Top SigView Alternatives

StarTree Cloud functions as a fully-managed platform for real-time analytics, optimized for online analytical processing (OLAP) with exceptional speed and scalability tailored for user-facing applications. Leveraging the capabilities of Apache Pinot, it offers enterprise-level reliability along with advanced features such as tiered storage, scalable upserts, and a variety of additional indexes and connectors. The platform seamlessly integrates with transactional databases and event streaming technologies, enabling the ingestion of millions of events per second while indexing them for rapid query performance. Available on popular public clouds or for private SaaS deployment, StarTree Cloud caters to diverse organizational needs. Included within StarTree Cloud is the StarTree Data Manager, which facilitates the ingestion of data from both real-time sources—such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda—and batch data sources like Snowflake, Delta Lake, Google BigQuery, or object storage solutions like Amazon S3, Apache Flink, Apache Hadoop, and Apache Spark. Moreover, the system is enhanced by StarTree ThirdEye, an anomaly detection feature that monitors vital business metrics, sends alerts, and supports real-time root-cause analysis, ensuring that organizations can respond swiftly to any emerging issues. This comprehensive suite of tools not only streamlines data management but also empowers organizations to maintain optimal performance and make informed decisions based on their analytics.

Improvado is an ETL platform designed to automate data pipelines for marketing teams, enabling users without technical expertise to harness the power of data. This tool empowers marketers to make strategic, data-informed decisions by providing a holistic approach to integrating marketing data throughout the organization. It efficiently extracts information from various marketing data sources, standardizes it, and loads it directly into user-friendly marketing dashboards. With more than 200 pre-built connectors available, Improvado ensures a wide array of integrations, and the dedicated team is also willing to develop new connectors upon client request. By utilizing Improvado, marketers can centralize their data, enhance their understanding of performance across different channels, evaluate attribution models, and access precise Return on Marketing Investment (ROMI) metrics. Well-known companies such as Asus, BayCare, and Monster Energy have adopted Improvado to strengthen their marketing efforts. This platform not only simplifies data management but also fosters a culture of data-driven decision-making within organizations.

Qrvey stands out as the sole provider of embedded analytics that features an integrated data lake. This innovative solution allows engineering teams to save both time and resources by seamlessly linking their data warehouse to their SaaS application through a ready-to-use platform. Qrvey's comprehensive full-stack offering equips engineering teams with essential tools, reducing the need for in-house software development. It is specifically designed for SaaS companies eager to enhance the analytics experience for multi-tenant environments. The advantages of Qrvey's solution include: - An integrated data lake powered by Elasticsearch, - A cohesive data pipeline for the ingestion and analysis of various data types, - An array of embedded components designed entirely in JavaScript, eliminating the need for iFrames, - Customization options that allow for tailored user experiences. With Qrvey, organizations can focus on developing less software while maximizing the value they deliver to their users, ultimately transforming their analytics capabilities. This empowers companies to foster deeper insights and improve decision-making processes.

Doolytic leads the way in big data discovery by merging data exploration, advanced analytics, and the extensive possibilities offered by big data. The company empowers proficient business intelligence users to engage in a revolutionary shift towards self-service big data exploration, revealing the data scientist within each individual. As a robust enterprise software solution, Doolytic provides built-in discovery features specifically tailored for big data settings. Utilizing state-of-the-art, scalable, open-source technologies, Doolytic guarantees rapid performance, effectively managing billions of records and petabytes of information with ease. It adeptly processes structured, unstructured, and real-time data from various sources, offering advanced query capabilities designed for expert users while seamlessly integrating with R for in-depth analytics and predictive modeling. Thanks to the adaptable architecture of Elastic, users can easily search, analyze, and visualize data from any format and source in real time. By leveraging the power of Hadoop data lakes, Doolytic overcomes latency and concurrency issues that typically plague business intelligence, paving the way for efficient big data discovery without cumbersome or inefficient methods. Consequently, organizations can harness Doolytic to fully unlock the vast potential of their data assets, ultimately driving innovation and informed decision-making.

Data integration for hybrid cloud environments ensures efficient and dependable synchronization between your private and public cloud infrastructures. This process occurs in real-time and employs change data capture along with streaming capabilities. Striim, created by a seasoned team from GoldenGate Software, boasts extensive expertise in managing essential enterprise tasks. It can be deployed as a distributed platform within your infrastructure or hosted entirely in the cloud. The scalability of Striim can be easily modified to meet your team's requirements. It adheres to stringent security standards, including HIPAA and GDPR compliance, ensuring data protection. Designed from its inception to cater to contemporary enterprise demands, Striim effectively handles workloads whether they reside on-premise or in the cloud. Users can effortlessly create data flows between various sources and targets using a simple drag-and-drop interface. Additionally, real-time SQL queries empower you to process, enrich, and analyze streaming data seamlessly, enhancing your operational efficiency. This flexibility fosters a more responsive approach to data management across diverse platforms.

A cutting-edge analytics platform driven by artificial intelligence empowers users with self-service capabilities for data examination. This solution effortlessly merges multiple data sources and allows for the creation of visual displays without any need for coding expertise. As a fully cloud-based application, it guarantees high-quality data provision and supports intelligent, real-time analysis organization-wide, all while remaining code-free. Users can easily link various data sources, regardless of their types, facilitating the identification of core problems. By significantly reducing the duration from data acquisition to targeted analysis, it enables individuals without technical skills to engage in analytics with ease. The platform provides real-time data refresh capabilities, allowing users to connect to sources in any format, stream data continuously or at predetermined intervals to a data lake, and visualize it through advanced interactive dashboards utilizing search engine technology. It integrates descriptive, predictive, and prescriptive analytics into a unified platform, capitalizing on the power of sophisticated visualization techniques. There is no requirement for obsolete technology to explore data in diverse visualization formats, and users can interact with their data by rolling up, slicing, and dicing it while executing various mathematical calculations directly within the Bizintel360 visualization setting. This forward-thinking methodology in analytics not only streamlines the process but also significantly enhances decision-making across the entire organization, paving the way for better outcomes. Moreover, the platform’s user-centric design ensures that even those new to data analysis can confidently navigate and derive insights from complex datasets.

Amazon EMR is recognized as a top-tier cloud-based big data platform that efficiently manages vast datasets by utilizing a range of open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This innovative platform allows users to perform Petabyte-scale analytics at a fraction of the cost associated with traditional on-premises solutions, delivering outcomes that can be over three times faster than standard Apache Spark tasks. For short-term projects, it offers the convenience of quickly starting and stopping clusters, ensuring you only pay for the time you actually use. In addition, for longer-term workloads, EMR supports the creation of highly available clusters that can automatically scale to meet changing demands. Moreover, if you already have established open-source tools like Apache Spark and Apache Hive, you can implement EMR on AWS Outposts to ensure seamless integration. Users also have access to various open-source machine learning frameworks, including Apache Spark MLlib, TensorFlow, and Apache MXNet, catering to their data analysis requirements. The platform's capabilities are further enhanced by seamless integration with Amazon SageMaker Studio, which facilitates comprehensive model training, analysis, and reporting. Consequently, Amazon EMR emerges as a flexible and economically viable choice for executing large-scale data operations in the cloud, making it an ideal option for organizations looking to optimize their data management strategies.

Apache Druid stands out as a robust open-source distributed data storage system that harmonizes elements from data warehousing, timeseries databases, and search technologies to facilitate superior performance in real-time analytics across diverse applications. The system's ingenious design incorporates critical attributes from these three domains, which is prominently reflected in its ingestion processes, storage methodologies, query execution, and overall architectural framework. By isolating and compressing individual columns, Druid adeptly retrieves only the data necessary for specific queries, which significantly enhances the speed of scanning, sorting, and grouping tasks. Moreover, the implementation of inverted indexes for string data considerably boosts the efficiency of search and filter operations. With readily available connectors for platforms such as Apache Kafka, HDFS, and AWS S3, Druid integrates effortlessly into existing data management workflows. Its intelligent partitioning approach markedly improves the speed of time-based queries when juxtaposed with traditional databases, yielding exceptional performance outcomes. Users benefit from the flexibility to easily scale their systems by adding or removing servers, as Druid autonomously manages the process of data rebalancing. In addition, its fault-tolerant architecture guarantees that the system can proficiently handle server failures, thus preserving operational stability. This resilience and adaptability make Druid a highly appealing option for organizations in search of dependable and efficient analytics solutions, ultimately driving better decision-making and insights.

GeoSpock transforms the landscape of data integration in a connected universe with its advanced GeoSpock DB, a state-of-the-art space-time analytics database. This cloud-based platform is crafted for optimal querying of real-world data scenarios, enabling the synergy of various Internet of Things (IoT) data sources to unlock their full potential while simplifying complexity and cutting costs. With the capabilities of GeoSpock DB, users gain from not only efficient data storage but also seamless integration and rapid programmatic access, all while being able to execute ANSI SQL queries and connect to analytics platforms via JDBC/ODBC connectors. Analysts can perform assessments and share insights utilizing familiar tools, maintaining compatibility with well-known business intelligence solutions such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, alongside support for data science and machine learning environments like Python Notebooks and Apache Spark. Additionally, the database allows for smooth integration with internal systems and web services, ensuring it works harmoniously with open-source and visualization libraries, including Kepler and Cesium.js, which broadens its applicability across different fields. This holistic approach not only enhances the ease of data management but also empowers organizations to make informed, data-driven decisions with confidence and agility. Ultimately, GeoSpock DB serves as a vital asset in optimizing operational efficiency and strategic planning.

BIRD Analytics stands out as an exceptionally swift and high-performance platform designed for thorough data management and analytics, empowering organizations to uncover insights through agile business intelligence and sophisticated AI/ML models. It covers all aspects of data management, from ingestion and transformation to wrangling, modeling, and real-time analysis, handling data even at a petabyte scale. Featuring self-service tools reminiscent of Google search and robust ChatBot integration, BIRD enhances the overall user experience. Our extensive collection of resources, including various case studies and informative blog posts, illustrates how BIRD successfully addresses the complexities associated with Big Data challenges. Recognizing the significant benefits BIRD offers, you have the opportunity to schedule a demo to see the platform's capabilities in action and discover how it can transform your specific data requirements. By harnessing AI/ML technologies, organizations can improve their agility and responsiveness in decision-making, lower operational costs, and enhance customer experiences, paving the way for a future that is increasingly driven by data. Moreover, embracing BIRD Analytics opens the door to discovering new avenues for innovation and operational efficiency that can set your organization apart in a competitive landscape.

Hydrolix acts as a sophisticated streaming data lake, combining separated storage, indexed search, and stream processing to facilitate swift query performance at a scale of terabytes while significantly reducing costs. Financial officers are particularly pleased with a substantial 4x reduction in data retention costs, while product teams enjoy having quadruple the data available for their needs. It’s simple to activate resources when required and scale down to nothing when they are not in use, ensuring flexibility. Moreover, you can fine-tune resource usage and performance to match each specific workload, leading to improved cost management. Envision the advantages for your initiatives when financial limitations no longer restrict your access to data. You can intake, enhance, and convert log data from various sources like Kafka, Kinesis, and HTTP, guaranteeing that you extract only essential information, irrespective of the data size. This strategy not only reduces latency and expenses but also eradicates timeouts and ineffective queries. With storage functioning independently from the processes of ingestion and querying, each component can scale independently to meet both performance and budgetary objectives. Additionally, Hydrolix's high-density compression (HDX) often compresses 1TB of data down to an impressive 55GB, optimizing storage usage. By utilizing these advanced features, organizations can fully unlock their data's potential without being hindered by financial limitations, paving the way for innovative solutions and insights that drive success.

IBM Db2 Big SQL serves as an advanced hybrid SQL-on-Hadoop engine designed to enable secure and sophisticated data queries across a variety of enterprise big data sources, including Hadoop, object storage, and data warehouses. This enterprise-level engine complies with ANSI standards and features massively parallel processing (MPP) capabilities, which significantly boost query performance. Users of Db2 Big SQL can run a single database query that connects multiple data sources, such as Hadoop HDFS, WebHDFS, relational and NoSQL databases, as well as object storage solutions. The engine boasts several benefits, including low latency, high efficiency, strong data security measures, adherence to SQL standards, and robust federation capabilities, making it suitable for both ad hoc and intricate queries. Currently, Db2 Big SQL is available in two formats: one that integrates with Cloudera Data Platform and another offered as a cloud-native service on the IBM Cloud Pak® for Data platform. This flexibility enables organizations to effectively access and analyze data, conducting queries on both batch and real-time datasets from diverse sources, thereby optimizing their data operations and enhancing decision-making. Ultimately, Db2 Big SQL stands out as a comprehensive solution for efficiently managing and querying large-scale datasets in an increasingly intricate data environment, thereby supporting organizations in navigating the complexities of their data strategy.

The PI System unlocks a wealth of operational insights and creates avenues for innovation. By delivering dependable and high-caliber operations data, it streamlines the journey toward digital transformation. This system enables data to be gathered, refined, and delivered in real-time from virtually any source. It equips engineers and operators with powerful tools while speeding up the analytical processes for data scientists. Furthermore, the PI System encourages new business opportunities through the aggregation of real-time information from a wide range of assets, including legacy systems, specialized equipment, remote devices, mobile technology, and IIoT innovations. It guarantees that users can retrieve their data regardless of where it resides or its format, thus facilitating the storage of extensive historical data at exceptional sub-second resolution. Organizations benefit from immediate access to high-fidelity historical, real-time, and predictive data, allowing them to uphold vital operations and extract significant business insights. By employing user-friendly labels and metadata, the data becomes more insightful, enabling users to create hierarchies that match their operational and reporting needs. This added context provides a comprehensive view, allowing individuals to connect data points to the larger narrative and make more educated choices. Consequently, the PI System not only boosts operational productivity but also propels strategic initiatives that have the potential to revolutionize entire industries. Ultimately, embracing the PI System can lead to a competitive advantage in a rapidly evolving market landscape.

Phocas delivers a comprehensive business intelligence (BI) and financial planning and analysis (FP&A) platform tailored for mid-market companies engaged in manufacturing, distribution, and sales. With a focus on empowering users to feel confident about their data, Phocas facilitates improved collaboration, understanding, and strategic planning among businesses. By integrating with ERP systems such as Epicor, Sage, and Oracle NetSuite, Phocas enhances their functionalities by merging various data sources—including ERP, CRM, and spreadsheets—into a singular, user-friendly platform that offers diverse tools for analysis, reporting, and planning. Its standout features encompass user-friendly dashboards, customizable reporting, dynamic financial statements, adaptable budgeting, precise forecasting, and automated management of rebates. With real-time data access and robust security measures, Phocas enables teams across different functions to delve into their data and make well-informed decisions with confidence. Designed for ease of use by all business users, Phocas streamlines data-related tasks by automating the consolidation of financial and operational information, which not only saves time but also minimizes the potential for errors. Whether it’s for generating month-end reports, identifying trends, overseeing cash flow, or enhancing rebate strategies, Phocas equips businesses with the insights necessary to maintain a competitive edge in the market. Additionally, this platform fosters an environment where data-driven decision-making becomes central to daily operations, ultimately transforming how organizations approach their strategic goals.

Riak is a specialist in distributed systems who collaborates with Application teams to tackle the complexities associated with these systems. Riak® is a distributed NoSQL database that provides: - Exceptional resilience that surpasses standard "high availability" solutions - Cutting-edge technology that guarantees data integrity, ensuring that no information is ever lost - Capability to scale massively on conventional hardware - A unified codebase that facilitates genuine multi-model support In addition to these features, Riak® prioritizes user-friendliness. Opt for Riak® KV for a versatile key-value data model suitable for managing web-scale profiles, session handling, real-time big data applications, catalog content management, comprehensive customer insights, digital messaging, and various other scenarios. Alternatively, select Riak® TS for applications related to IoT, time series analysis, and additional use cases, thereby enhancing your system's efficiency and performance.

Dataproc significantly improves the efficiency, ease, and safety of processing open-source data and analytics in a cloud environment. Users can quickly establish customized OSS clusters on specially configured machines to suit their unique requirements. Whether additional memory for Presto is needed or GPUs for machine learning tasks in Apache Spark, Dataproc enables the swift creation of tailored clusters in just 90 seconds. The platform features simple and economical options for managing clusters. With functionalities like autoscaling, automatic removal of inactive clusters, and billing by the second, it effectively reduces the total ownership costs associated with OSS, allowing for better allocation of time and resources. Built-in security protocols, including default encryption, ensure that all data remains secure at all times. The JobsAPI and Component Gateway provide a user-friendly way to manage permissions for Cloud IAM clusters, eliminating the need for complex networking or gateway node setups and thus ensuring a seamless experience. Furthermore, the intuitive interface of the platform streamlines the management process, making it user-friendly for individuals across all levels of expertise. Overall, Dataproc empowers users to focus more on their projects rather than on the complexities of cluster management.

Kyligence Zen enables the collection, organization, and analysis of your metrics, allowing you to focus more on taking actionable steps. As a low-code metrics platform, Kyligence Zen is an ideal solution for defining, gathering, and analyzing business metrics efficiently. Users can easily connect to their data sources, establish business metrics in just a few minutes, reveal hidden insights, and disseminate this valuable information throughout their organization. Kyligence Enterprise provides a range of solutions tailored for public cloud, on-premises, and private cloud environments, catering to enterprises of all sizes. This flexibility allows businesses to conduct multidimensional analyses of large data sets based on their specific requirements. Built on Apache Kylin, Kyligence Enterprise facilitates sub-second SQL queries across PB-scale datasets, streamlining the analysis of complex data for companies. This capability empowers organizations to swiftly uncover the business value hidden within vast amounts of data, ultimately leading to more informed and impactful business decisions. By leveraging such advanced tools, companies can transform their data into actionable insights, driving growth and efficiency.

Unlock critical insights by leveraging a diverse collection of human-generated data. This encompasses a wide range of information from social media channels, blogs, news articles, and various other sources. By merging social, blog, and news data into a unified system, you gain access to both current and past information drawn from billions of data points. The platform swiftly processes and refines this data, guaranteeing accurate analysis. With DataSift, you can effortlessly incorporate Human Data into your business intelligence (BI) systems and operational processes in real-time. Additionally, our powerful API allows for the development of customized applications that meet your specific requirements. Human Data is the fastest-growing segment of information, covering all varieties of content produced by people, regardless of its format or medium. This includes text, images, audio, and video disseminated across social platforms, blogs, news organizations, and within corporate settings. The DataSift Human Data platform consolidates these varied data sources—both real-time and historical—into one centralized hub, uncovering their importance and facilitating their use across your business environment. By utilizing this data effectively, organizations can foster innovation and make well-informed decisions, ultimately enhancing their competitive edge in the market. Embracing this wealth of information can transform how businesses operate and strategize in today’s data-driven world.

Keen operates as a comprehensive event streaming platform that is fully managed. By utilizing a real-time data pipeline built on Apache Kafka, it simplifies the process of gathering significant volumes of event data. The robust REST APIs and SDKs provided by Keen enable event data collection from any internet-connected device, enhancing versatility and accessibility. Additionally, our platform ensures the secure storage of your data, effectively minimizing operational and delivery risks associated with data handling. The use of Apache Cassandra's storage framework guarantees that your data remains secure during transit through HTTPS and TLS protocols. Furthermore, this data is safeguarded with multilayer AES encryption, reinforcing its protection. With Access Keys, you can present data in flexible formats without needing to overhaul or restructure the existing data model. The implementation of Role-based Access Control provides the ability to define customizable permission levels, allowing for granular control down to specific queries or individual data points. This level of flexibility in user access is crucial for maintaining both security and efficiency in data management.

Seamlessly harness your organization's data with our SHREWD Platform, which boasts sophisticated tools and open APIs. The SHREWD Platform is tailored with integration and data collection capabilities that enhance the functionality of multiple SHREWD modules. These capabilities aggregate data and securely archive it in a UK-based data lake. Afterward, this data can be accessed by SHREWD modules or via an API, transforming raw data into actionable insights specifically customized for unique requirements. The platform accommodates data ingestion in nearly any format, whether from traditional spreadsheets or contemporary digital systems utilizing APIs. Moreover, its open API allows for third-party integrations, giving external applications the ability to tap into the information stored within the data lake when needed. By establishing an operational data layer that acts as a real-time single source of truth, the SHREWD Platform enables its modules to provide valuable analytics, allowing managers and decision-makers to respond swiftly and effectively. This comprehensive data management strategy not only streamlines operations but also ensures that organizations can adapt promptly to evolving market needs, thereby enhancing overall agility and responsiveness.

Smart DIH is a robust data management solution that efficiently provides applications with precise, up-to-date, and comprehensive data, ensuring excellent performance, minimal latency, and a continuously available digital experience. By separating APIs from systems of record, Smart DIH replicates essential data and makes it accessible through an event-driven framework. This innovative approach allows for significantly reduced development timelines for new digital services and enables the platform to effortlessly accommodate millions of simultaneous users, regardless of the underlying IT infrastructure or cloud configurations. On the other hand, XAP Skyline stands out as a distributed in-memory development platform that guarantees transactional integrity while delivering high-speed event-driven processing with microsecond response times. It powers critical business applications that depend on real-time data, such as online trading systems, immediate risk assessment, and data processing for artificial intelligence and advanced language models. This combination of capabilities makes both platforms essential for modern digital enterprises aiming for agility and efficiency.

Talend Data Fabric's cloud offerings proficiently address all your integration and data integrity challenges, whether on-premises or in the cloud, connecting any source to any endpoint seamlessly. Reliable data is available at the right moment for every user, ensuring timely access to critical information. Featuring an intuitive interface that requires minimal coding, the platform enables users to swiftly integrate data, files, applications, events, and APIs from a variety of sources to any desired location. By embedding quality into data management practices, organizations can ensure adherence to all regulatory standards. This can be achieved through a collaborative, widespread, and unified strategy for data governance. Access to high-quality, trustworthy data is vital for making well-informed decisions, and it should be sourced from both real-time and batch processing, supplemented by top-tier data enrichment and cleansing tools. Enhancing the value of your data is accomplished by making it accessible to both internal teams and external stakeholders alike. The platform's comprehensive self-service capabilities simplify the process of building APIs, thereby fostering improved customer engagement and satisfaction. Furthermore, this increased accessibility contributes to a more agile and responsive business environment.

bi(OS)® provides an unparalleled speed to insight for developers engaged in crafting data applications in a unified manner. Utilizing bi(OS)®, the entire development cycle of data applications can be accomplished in mere hours to a few days. This all-encompassing approach includes the seamless integration of varied data sources, the extraction of real-time insights, and the effortless deployment into production settings. Collaborating with enterprise data teams across multiple industries allows you to evolve into the data champion your organization requires. Despite the combination of Open Source, Cloud, and SaaS, the true potential for achieving authentic data-driven outcomes remains largely unrealized. Many enterprises have concentrated their resources on data movement and integration, a tactic that proves to be ultimately unsustainable. A new outlook on data management is critically needed, one that addresses the specific challenges faced by enterprises. bi(OS)® is conceived by reexamining essential principles in enterprise data management, encompassing everything from data ingestion to insight development. It effectively serves the needs of API, AI, and BI developers in a unified manner, facilitating data-driven results within a matter of days. As engineers work together efficiently, a synergistic relationship develops among IT teams, tools, and processes, which fosters a sustainable competitive edge for the organization. This innovative approach not only streamlines workflows but also empowers teams to harness the full potential of their data assets.

Streamline your operations and cut costs by utilizing straightforward open-source solutions to simplify your data pipelines. From the initial stages of data ingestion to final visualization, every element is cohesively integrated, managed entirely, and highly dependable, ensuring that your engineering team finds joy in handling data. You have the choice of using any of DoubleCloud’s managed open-source services or leveraging the full range of the platform’s features, which encompass data storage, orchestration, ELT, and real-time visualization capabilities. We provide top-tier open-source services including ClickHouse, Kafka, and Airflow, which can be deployed on platforms such as Amazon Web Services or Google Cloud. Additionally, our no-code ELT tool facilitates immediate data synchronization across different systems, offering a rapid, serverless solution that meshes seamlessly with your current infrastructure. With our managed open-source data visualization tools, generating real-time visual interpretations of your data through interactive charts and dashboards is a breeze. Our platform is specifically designed to optimize the daily workflows of engineers, making their tasks not only more efficient but also more enjoyable. Ultimately, this emphasis on user-friendliness and convenience is what distinguishes us from competitors in the market. We believe that a better experience leads to greater productivity and innovation within teams.

Inzata Analytics is a comprehensive data analytics software solution driven by artificial intelligence. It seamlessly converts raw data into actionable insights through a unified platform, allowing you to establish your complete data warehouse in just minutes. With more than 700 data connectors, Inzata simplifies and accelerates the process of data integration. Its patented aggregation engine ensures that pre-blended, blended, and organized data models are available in mere seconds. The innovative InFlow tool enables users to automate data pipeline workflows, facilitating real-time updates for data analysis. Additionally, you can utilize fully customizable interactive dashboards to showcase your business intelligence effectively. By harnessing the capabilities of Inzata, businesses gain the advantage of real-time analytics, enhancing their agility and ability to respond to changing market conditions. This transformative approach empowers organizations to make informed decisions swiftly and efficiently.

DataMax serves as a powerful solution tailored for enterprises, streamlining the complex elements of managing real-time data, which allows organizations to build, launch, and function efficiently at scale. This platform accelerates the pace at which companies can enact changes. With its unique architecture, methodologies, and a combination of advanced technologies, DataMax transforms fragmented data and reporting systems into a unified and comprehensive data perspective, providing essential insights for optimizing operations. Its innovative fusion of technologies guarantees effective data management that meets the rigorous demands of enterprises. The system has proven its ability to scale effectively and is specifically designed for cloud-based applications, supporting both time series and non-time series data seamlessly. By creating analytics frameworks, it significantly improves the quality of data, analysis, and reporting available to market analytics teams, thus enhancing the decision-making prowess of traders. In doing so, DataMax not only empowers organizations to adapt quickly to market fluctuations but also fosters the enhancement of their overall business strategies and operational efficiency. Furthermore, this robust platform positions businesses to leverage data as a strategic asset, ultimately driving growth and innovation.

Enterprise Enabler consolidates diverse information from multiple sources and fragmented data sets into a single, cohesive platform; this encompasses data stored in the cloud, scattered across standalone databases, kept on various instruments, residing in Big Data repositories, or found within numerous spreadsheets and documents. By facilitating seamless integration of all your data, it equips you to make prompt and informed business decisions. The system constructs logical representations of data from its original sources, allowing you to effectively reuse, configure, test, deploy, and monitor everything within one unified environment. This capability enables you to analyze your business data as events progress, which aids in optimizing asset utilization, lowering costs, and refining your business processes. Notably, our deployment timeline is generally 50-90% faster, ensuring that your data sources are interconnected and functioning in a remarkably short period, thus supporting real-time decision-making based on the latest available information. With this innovative solution, organizations can boost collaboration and efficiency, resulting in enhanced overall performance and a competitive edge in the marketplace. Additionally, this strategic integration fosters a culture of data-driven insights, empowering teams to innovate and adapt swiftly to market changes.

Introducing a cutting-edge digital manufacturing platform powered by the Internet of Things, Datonis provides out-of-the-box applications that streamline the processes of monitoring, measurement, analysis, and outcome forecasting by leveraging artificial intelligence capabilities. This platform embraces a comprehensive methodology to unify IT and operational technology systems, thus allowing for the monetization of specialized knowledge through the creation of innovative applications and services. It features inter-plant process benchmarking and predictive quality assurance models, complemented by real-time compliance monitoring for quality audits. The system sends alerts related to process compliance, trends in Cpk, and tracks instances of quality rejections and scrap, while also establishing connections between various processes and defects. Furthermore, the platform alerts users to violations of checklist schedules, performs trend analyses on checklist data, and offers a versatile framework for generating various types of checklists. Users can receive notifications for checklists, document observations via mobile devices, and review images and videos prior to making decisions about checklist items. An interactive application is also available for operators, allowing them to interact with the platform and monitor progress in real-time, while the operator workbench empowers them to provide feedback, raise alarms, seek assistance, and access necessary engineering documentation. This thorough integration not only boosts operational efficiency but also cultivates a culture of ongoing improvement within manufacturing processes, encouraging a proactive approach to quality management. Ultimately, Datonis stands as a transformative force in digital manufacturing, driving innovation and enhancing productivity across industries.

Anodot harnesses the power of AI to provide autonomous analytics on an enterprise scale, accommodating all types of data in real-time. Our platform empowers business analysts to gain control over their operations, transcending the constraints of conventional Business Intelligence. Operating continuously, our self-service AI technology eradicates blind spots, sends alerts for incidents, and aids in root cause investigations. Utilizing patent-pending machine learning algorithms, the platform accurately identifies problems and correlates them across various parameters, thereby eliminating delays in business insights and facilitating rapid, informed decision-making. Anodot caters to more than 100 clients in the digital transformation sector, including notable names like Microsoft, Lyft, and Waze, spanning industries such as eCommerce, FinTech, AdTech, telecommunications, and gaming. Founded in 2014 with roots in Silicon Valley and Israel, Anodot also maintains a presence with sales offices globally, demonstrating its commitment to serving a diverse international clientele. As the demand for agile analytics grows, Anodot continues to innovate and expand its offerings.

Deepnote is creating an exceptional data science notebook designed specifically for collaborative teams. You can seamlessly connect to your data, delve into analysis, and collaborate in real time while benefiting from version control. Additionally, you can easily share project links with fellow analysts and data scientists or showcase your refined notebooks to stakeholders and end users. This entire experience is facilitated through a robust, cloud-based user interface that operates directly in your browser, making it accessible and efficient for all. Ultimately, Deepnote aims to enhance productivity and streamline the data science workflow within teams.

Leverage Azure Resource Manager to quickly create and deploy an Azure Analysis Services instance, which allows for the efficient backup and restoration of your existing models to the cloud platform, thus taking advantage of its scalability, flexibility, and management features. This service can be easily adjusted in terms of scale—whether you need to increase, decrease, or temporarily halt operations—ensuring that you only pay for the resources you actually use. By integrating data from various sources into a unified and user-friendly BI semantic model, you can promote clarity and ease of access. This method enhances self-service capabilities and encourages data exploration among business users by simplifying both the presentation of data and its underlying structure. As a result, the time needed to generate insights from large and complex datasets is significantly reduced, while quick response capabilities ensure that your BI solutions meet the needs of business users and adapt to changing requirements. Additionally, you can connect to real-time operational data through DirectQuery, keeping you informed about the dynamics within your organization, and utilize your preferred data visualization tools to bring these insights to life, fostering a deeper understanding of your data landscape. This comprehensive approach not only supports better decision-making but also encourages a culture of data-driven insights throughout the organization.

Scuba facilitates widespread self-service analytics, accommodating a diverse range of professionals, including product managers, business unit leaders, chief experience officers, data scientists, business analysts, and IT staff, all of whom can easily access their data to derive meaningful insights. With Interana, you can deepen your understanding of customer interactions, system efficiency, and application usage, going beyond conventional dashboards and static reports. This innovative analytics tool allows you and your team to explore data dynamically in real-time, shedding light on not only current business activities but also the reasons behind them. Scuba ensures immediate access to data, enabling you to ask questions as they arise without any delays. Tailored for everyday business users, Scuba removes the barriers of coding or SQL expertise, making data exploration universally accessible. As a result, organizations can make prompt and informed decisions grounded in real-time insights, rather than relying on obsolete data. Ultimately, this empowers teams to adapt swiftly to changes in the business landscape, enhancing overall agility and responsiveness.

TAMI offers an unparalleled and precise overview of your market, granting you direct access to 130 million companies and more than 532 million verified business contacts. Our services are fully compliant with GDPR regulations, and we focus on European data, utilizing patented technology in the region. By leveraging our platform, you can optimize your sales strategy and significantly enhance the effectiveness of your team's prospecting initiatives, ultimately leading to greater success in your business endeavors.

EMR functions as a robust big data platform tailored for enterprise needs, providing essential features for cluster, job, and data management while utilizing a variety of open-source technologies such as Hadoop, Spark, Kafka, Flink, and Storm. Specifically crafted for big data processing within the Alibaba Cloud framework, Alibaba Cloud Elastic MapReduce (EMR) is built upon Alibaba Cloud's ECS instances and incorporates the strengths of Apache Hadoop and Apache Spark. This platform empowers users to take advantage of the extensive components available in the Hadoop and Spark ecosystems, including tools like Apache Hive, Apache Kafka, Flink, Druid, and TensorFlow, facilitating efficient data analysis and processing. Users benefit from the ability to seamlessly manage data stored in different Alibaba Cloud storage services, including Object Storage Service (OSS), Log Service (SLS), and Relational Database Service (RDS). Furthermore, EMR streamlines the process of cluster setup, enabling users to quickly establish clusters without the complexities of hardware and software configuration. The platform's maintenance tasks can be efficiently handled through an intuitive web interface, ensuring accessibility for a diverse range of users, regardless of their technical background. This ease of use encourages a broader adoption of big data processing capabilities across different industries.

Embark on a comprehensive journey of crafting machine learning algorithms and predicting outcomes with remarkable ease in just one click. It's important to recognize that not every dataset is ideal for machine learning applications; utilize the Data Dialog to seamlessly enhance your data without the need for tedious file edits. Share your prediction reports effortlessly with your team or opt for public access, enabling anyone to interact with your model and produce their own forecasts. Through our intuitive low-code API, you can incorporate dynamic ML predictions directly into your applications. Evaluate important metrics such as willingness to pay, assess potential leads, and conduct various analyses in real-time. Obviously AI provides cutting-edge algorithms while ensuring high performance throughout the process. Accurately project revenue, optimize supply chain management, and customize marketing strategies according to specific consumer needs. With a simple CSV upload or a swift integration with your preferred data sources, you can easily choose your prediction column from a user-friendly dropdown and observe as the AI is automatically built for you. Furthermore, benefit from beautifully designed visual representations of predicted results, pinpoint key influencers, and delve into "what-if" scenarios to gain insights into possible future outcomes. This revolutionary approach not only enhances your data interaction but also elevates the standard for predictive analytics in your organization.

Apache Storm is a robust open-source framework designed for distributed real-time computations, enabling the reliable handling of endless streams of data, much like how Hadoop transformed the landscape of batch processing. This platform boasts a user-friendly interface, supports multiple programming languages, and offers an enjoyable user experience. Its wide-ranging applications encompass real-time analytics, ongoing computations, online machine learning, distributed remote procedure calls, and the processes of extraction, transformation, and loading (ETL). Notably, performance tests indicate that Apache Storm can achieve processing speeds exceeding one million tuples per second per node, highlighting its remarkable efficiency. Furthermore, the system is built to be both scalable and fault-tolerant, guaranteeing uninterrupted data processing while remaining easy to install and manage. Apache Storm also integrates smoothly with existing queuing systems and various database technologies, enhancing its versatility. Within a typical setup, data streams are managed and processed through a topology capable of complex operations, which facilitates the flexible repartitioning of data at different computation stages. For further insights, a detailed tutorial is accessible online, making it an invaluable resource for users. Consequently, Apache Storm stands out as an exceptional option for organizations eager to harness the power of real-time data processing capabilities effectively.

Delta Lake acts as an open-source storage solution that integrates ACID transactions within Apache Spark™ and enhances operations in big data environments. In conventional data lakes, various pipelines function concurrently to read and write data, often requiring data engineers to invest considerable time and effort into preserving data integrity due to the lack of transactional support. With the implementation of ACID transactions, Delta Lake significantly improves data lakes, providing a high level of consistency thanks to its serializability feature, which represents the highest standard of isolation. For more detailed exploration, you can refer to Diving into Delta Lake: Unpacking the Transaction Log. In the big data landscape, even metadata can become quite large, and Delta Lake treats metadata with the same importance as the data itself, leveraging Spark's distributed processing capabilities for effective management. As a result, Delta Lake can handle enormous tables that scale to petabytes, containing billions of partitions and files with ease. Moreover, Delta Lake's provision for data snapshots empowers developers to access and restore previous versions of data, making audits, rollbacks, or experimental replication straightforward, while simultaneously ensuring data reliability and consistency throughout the system. This comprehensive approach not only streamlines data management but also enhances operational efficiency in data-intensive applications.

Revolutionize your perception of time in the realm of data analytics. With near-instant access to your business data, you can work directly from your dashboard without the constant need to rely on the IT department. Enter Indexima DataHub, a groundbreaking platform that empowers both operational staff and functional users to swiftly retrieve their data. By combining a specialized indexing engine with advanced machine learning techniques, Indexima allows organizations to enhance and expedite their analytics workflows. Built for durability and scalability, this solution enables firms to run queries on extensive datasets—potentially encompassing tens of billions of rows—in just milliseconds. The Indexima platform provides immediate analytics on all your data with a single click. Furthermore, with the introduction of Indexima's ROI and TCO calculator, you can determine the return on investment for your data platform in just half a minute, factoring in infrastructure costs, project timelines, and data engineering expenses while improving your analytical capabilities. Embrace the next generation of data analytics and unlock extraordinary efficiency in your business operations, paving the way for informed decision-making and strategic growth.

Oracle Cloud Infrastructure (OCI) Data Flow is an all-encompassing managed service designed for Apache Spark, allowing users to run processing tasks on vast amounts of data without the hassle of infrastructure deployment or management. By leveraging this service, developers can accelerate application delivery, focusing on app development rather than infrastructure issues. OCI Data Flow takes care of infrastructure provisioning, network configurations, and teardown once Spark jobs are complete, managing storage and security as well to greatly minimize the effort involved in creating and maintaining Spark applications for extensive data analysis. Additionally, with OCI Data Flow, the absence of clusters that need to be installed, patched, or upgraded leads to significant time savings and lower operational costs for various initiatives. Each Spark job utilizes private dedicated resources, eliminating the need for prior capacity planning. This results in organizations being able to adopt a pay-as-you-go pricing model, incurring costs solely for the infrastructure used during Spark job execution. Such a forward-thinking approach not only simplifies processes but also significantly boosts scalability and flexibility for applications driven by data. Ultimately, OCI Data Flow empowers businesses to unlock the full potential of their data processing capabilities while minimizing overhead.

We are thrilled to unveil an innovative big data platform tailored for the music industry, which merges all essential information into a single, trustworthy resource to guide strategic choices. In the realm of the music business, there are a multitude of data sources available, yet they frequently exist in isolation and lack cohesion. Our cutting-edge platform adeptly identifies and integrates these disparate sources, creating a solid foundation of high-quality data that can be utilized in the daily operations of the music industry. To function effectively and securely while revealing unique insights, record labels and agencies require a sophisticated data management and governance structure that guarantees data remains consistently accessible, relevant, and actionable. By incorporating various data sources into Wavo’s Big Data Platform, machine learning methodologies are employed to classify the data based on tailored templates, making it easier to access and deeply explore vital information. This functionality empowers every individual within a music organization to leverage and utilize data that is curated and structured for prompt implementation and value generation. Furthermore, our platform not only enhances decision-making but also drives improved operational efficiency throughout the entire music business ecosystem, ultimately transforming how organizations interact with and benefit from their data.

Efficiently ingesting, preparing, and managing data pipelines at scale is critical for cloud-based AI and analytics. Informatica's extensive data engineering suite provides users with a comprehensive array of tools essential for executing large-scale data engineering tasks that facilitate AI and analytical insights, incorporating features like advanced data integration, quality assurance, streaming capabilities, data masking, and preparation functionalities. Through CLAIRE®-driven automation, users can rapidly create intelligent data pipelines that incorporate automatic change data capture (CDC), enabling the ingestion of numerous databases and millions of files along with streaming events. This methodology significantly accelerates the return on investment by facilitating self-service access to trustworthy, high-quality data. Users can gain authentic perspectives on Informatica's data engineering solutions from reliable industry peers. Moreover, reference architectures tailored for sustainable data engineering practices can be explored to enhance efficiency. By adopting AI-driven data engineering in the cloud, organizations can guarantee that their analysts and data scientists have the reliable, high-quality data necessary for effectively transforming their business operations. This comprehensive strategy not only simplifies data management but also empowers teams to confidently make data-driven decisions, ultimately paving the way for innovative business solutions. In conclusion, leveraging such advanced tools and practices positions organizations to thrive in an increasingly data-centric landscape.

The surge in data-driven decision-making has led to a notable increase in the volume of business data and a growing need for its analysis. As a result, IT departments are shifting away from expensive Enterprise Data Warehouses (EDW) towards more cost-effective Big Data platforms like Hadoop or AWS, which offer a Total Cost of Ownership (TCO) that is roughly ten times lower. However, these newer systems face challenges when it comes to supporting interactive business intelligence (BI) applications, as they often fail to deliver the performance and user concurrency levels that traditional EDWs provide. To remedy this issue, Jethro was developed to facilitate interactive BI on Big Data without requiring any alterations to existing applications or data architectures. Acting as a transparent middle tier, Jethro eliminates the need for ongoing maintenance and operates autonomously. It also ensures compatibility with a variety of BI tools such as Tableau, Qlik, and Microstrategy, while remaining agnostic regarding data sources. By meeting the demands of business users, Jethro enables thousands of concurrent users to perform complex queries across billions of records efficiently, thereby boosting overall productivity and enhancing decision-making capabilities. This groundbreaking solution marks a significant leap forward in the realm of data analytics and sets a new standard for how organizations approach their data challenges. As businesses increasingly rely on data to drive strategies, tools like Jethro will play a crucial role in bridging the gap between Big Data and actionable insights.

A database designed with an in-memory, columnar structure and a Massively Parallel Processing (MPP) framework allows for the swift execution of queries on billions of records in just seconds. By distributing query loads across all nodes within a cluster, it provides linear scalability, which supports an increasing number of users while enabling advanced analytics capabilities. The combination of MPP architecture, in-memory processing, and columnar storage results in a system that is finely tuned for outstanding performance in data analytics. With various deployment models such as SaaS, cloud, on-premises, and hybrid, organizations can perform data analysis in a range of environments that suit their needs. The automatic query tuning feature not only lessens the required maintenance but also diminishes operational costs. Furthermore, the integration and performance efficiency of this database present enhanced capabilities at a cost significantly lower than traditional setups. Remarkably, innovative in-memory query processing has allowed a social networking firm to improve its performance, processing an astounding 10 billion data sets each year. This unified data repository, coupled with a high-speed processing engine, accelerates vital analytics, ultimately contributing to better patient outcomes and enhanced financial performance for the organization. Thus, organizations can harness this technology for more timely, data-driven decision-making, leading to greater success and a competitive edge in the market. Moreover, such advancements in technology are setting new benchmarks for efficiency and effectiveness in various industries.

kdb Insights is a cloud-based advanced analytics platform designed for rapid, real-time evaluation of both current and historical data streams. It enables users to make well-informed decisions quickly, irrespective of data volume or speed, and offers a remarkable price-performance ratio, delivering analytics that is up to 100 times faster while costing only 10% compared to other alternatives. The platform features interactive visualizations through dynamic dashboards, which facilitate immediate insights that are essential for prompt decision-making. Furthermore, it utilizes machine learning models to enhance predictive capabilities, identify clusters, detect patterns, and assess structured data, ultimately boosting AI functionalities with time-series datasets. With its impressive scalability, kdb Insights can handle enormous volumes of real-time and historical data, efficiently managing loads of up to 110 terabytes each day. Its swift deployment and easy data ingestion processes significantly shorten the time required to gain value, while also supporting q, SQL, and Python natively, and providing compatibility with other programming languages via RESTful APIs. This flexibility allows users to seamlessly incorporate kdb Insights into their current workflows, maximizing its potential for various analytical tasks and enhancing overall operational efficiency. Additionally, the platform's robust architecture ensures that it can adapt to future data challenges, making it a sustainable choice for long-term analytics needs.

Toustone is a collective of data specialists dedicated to transforming businesses into data-centric entities. Situated in Albury-Wodonga in regional Australia, the team has crafted a business intelligence solution that caters to a diverse range of sectors. It effectively tackles issues related to productivity, data transparency, unity, and trust, empowering organizations to make enhanced, informed decisions based on data. Their tailored offerings include: * Hosting & Data Warehousing * Data Modelling & Visualisation * AI & Data Science * Fully Managed Service This all-encompassing, customizable solution leverages extensive industry expertise, enabling businesses to generate automated daily KPI reports or visual dashboards. As a result, users can swiftly explore the underlying reasons behind their metrics and derive significant, actionable insights. To embark on your path towards a data-driven future, reach out to Toustone today and discover the possibilities that await your business. It’s the first step in harnessing the full potential of your data.

DataLux stands out as a cutting-edge platform tailored for proficient data management and analytics, crafted to address a range of data challenges while enabling swift decision-making. With its intuitive plug-and-play adaptors, users can easily consolidate vast data sets and visualize insights in real time. The platform’s data lake feature allows organizations to forecast and stimulate innovative developments while ensuring optimal data storage for accurate modeling. It facilitates the creation of portable applications through containerization, adaptable for public cloud, private cloud, or on-premises setups. DataLux adeptly integrates a variety of time-series market data and inferred metrics, such as stock exchange tick data, market policy changes, pertinent cross-industry news, and alternative datasets, to extract causal relationships influencing stock markets and macroeconomic variables. By offering these crucial insights, DataLux equips businesses to make informed decisions and drive product innovation effectively. Moreover, it enhances the product development lifecycle by supporting interdisciplinary A/B testing from conception to final decision-making, thus promoting a thorough enhancement of both design and engineering practices. This comprehensive functionality not only streamlines operations but also positions organizations to stay ahead in a competitive landscape.

USEReady is a New York-based firm specializing in data, analytics, and AI solutions. Boasting more than ten years of expertise, the company aids organizations in converting their data into meaningful insights that facilitate the attainment of business objectives. Among its offerings are migration automation tools such as STORM and MigratorIQ, in addition to Pixel Perfect, which enhances enterprise reporting capabilities. Furthermore, USEReady operates two key practices: Data Value, which emphasizes modern data architectures and BI & AI initiatives, and Decision Intelligence, which focuses on enabling informed decision-making and driving successful business outcomes through artificial intelligence, reinforcing its commitment to data-driven transformation. With a global workforce exceeding 450 professionals and locations in the United States, Canada, India, and Singapore, USEReady has provided services to over 300 clients, including numerous Fortune 500 companies spanning a variety of sectors. The firm collaborates with industry leaders such as Tableau, Salesforce, Snowflake, Starburst, and AWS, earning multiple accolades, including the prestigious title of Tableau Partner of the Year. As a result, USEReady continues to solidify its position as a leader in the data and analytics domain.

Lentiq provides a collaborative data lake service that empowers small teams to achieve remarkable outcomes. This platform enables users to quickly perform data science, machine learning, and data analysis on their preferred cloud infrastructure. With Lentiq, teams can easily ingest data in real-time, process and cleanse it, and share their insights with minimal effort. Additionally, it supports the creation, training, and internal sharing of models, fostering an environment where data teams can innovate and collaborate without constraints. Data lakes are adaptable environments for storage and processing, featuring capabilities like machine learning, ETL, and schema-on-read querying. For those exploring the field of data science, leveraging a data lake is crucial for success. In an era defined by the decline of large, centralized data lakes post-Hadoop, Lentiq introduces a novel concept of data pools—interconnected mini-data lakes spanning various clouds—that function together to create a secure, stable, and efficient platform for data science activities. This fresh approach significantly boosts the agility and productivity of data-driven initiatives, making it an essential tool for modern data teams. By embracing this innovative model, organizations can stay ahead in the ever-evolving landscape of data management.

The LogIsland platform is at the heart of Hurence's real-time analytics framework, allowing for the aggregation of factory events from the Industrial Internet of Things (IIoT) alongside data sourced from websites. Hurence claims that both manufacturing facilities and enterprises can be continuously monitored and analyzed through the extensive range of events they encounter, with each instance—such as a sales transaction, a robot completing a production task, or a product being shipped—considered an event. In essence, every action is classified as an event, and the LogIsland platform efficiently captures these occurrences, structuring them within a message bus designed to manage large data volumes. This infrastructure enables real-time analytical capabilities through a variety of plug-and-play analyzers, which range from simple tasks like counting and alert notifications to sophisticated artificial intelligence models that focus on predictive analytics and the detection of anomalies or defects. Moreover, this platform serves as a comprehensive solution for real-time event analysis, featuring custom analyzers specifically designed for web analytics and Industry 4.0, thus significantly improving decision-making processes across different sectors. By integrating diverse data streams and providing actionable insights, LogIsland empowers businesses to respond swiftly to changing conditions in their operational environment.

biGENIUS streamlines every aspect of analytic data management solutions, such as data lakes, data warehouses, and data marts, enabling you to transform your data into actionable business insights efficiently and economically. By employing these data analytics solutions, you can conserve valuable time, reduce effort, and lower costs. The platform facilitates the seamless incorporation of fresh ideas and data into your analytic frameworks. Utilizing a metadata-driven strategy enables you to leverage the latest technological advancements effectively. As digitalization progresses, traditional data warehouses and business intelligence systems must evolve to manage the growing volume of data effectively. Therefore, effective analytical data management has become crucial for contemporary business decision-making. This approach must incorporate new data sources, adapt to emerging technologies, and provide efficient solutions at an unprecedented speed, ideally while utilizing minimal resources. In this rapidly changing landscape, the ability to swiftly adjust to new requirements will determine the success of businesses.