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DataBuckEnsuring the integrity of Big Data Quality is crucial for maintaining data that is secure, precise, and comprehensive. As data transitions across various IT infrastructures or is housed within Data Lakes, it faces significant challenges in reliability. The primary Big Data issues include: (i) Unidentified inaccuracies in the incoming data, (ii) the desynchronization of multiple data sources over time, (iii) unanticipated structural changes to data in downstream operations, and (iv) the complications arising from diverse IT platforms like Hadoop, Data Warehouses, and Cloud systems. When data shifts between these systems, such as moving from a Data Warehouse to a Hadoop ecosystem, NoSQL database, or Cloud services, it can encounter unforeseen problems. Additionally, data may fluctuate unexpectedly due to ineffective processes, haphazard data governance, poor storage solutions, and a lack of oversight regarding certain data sources, particularly those from external vendors. To address these challenges, DataBuck serves as an autonomous, self-learning validation and data matching tool specifically designed for Big Data Quality. By utilizing advanced algorithms, DataBuck enhances the verification process, ensuring a higher level of data trustworthiness and reliability throughout its lifecycle.
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SatoriSatori is an innovative Data Security Platform (DSP) designed to facilitate self-service data access and analytics for businesses that rely heavily on data. Users of Satori benefit from a dedicated personal data portal, where they can effortlessly view and access all available datasets, resulting in a significant reduction in the time it takes for data consumers to obtain data from weeks to mere seconds. The platform smartly implements the necessary security and access policies, which helps to minimize the need for manual data engineering tasks. Through a single, centralized console, Satori effectively manages various aspects such as access control, permissions, security measures, and compliance regulations. Additionally, it continuously monitors and classifies sensitive information across all types of data storage—including databases, data lakes, and data warehouses—while dynamically tracking how data is utilized and enforcing applicable security policies. As a result, Satori empowers organizations to scale their data usage throughout the enterprise, all while ensuring adherence to stringent data security and compliance standards, fostering a culture of data-driven decision-making.
What is Enterprise Enabler?
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.
What is Actian Avalanche?
Actian Avalanche serves as a robust hybrid cloud data warehouse solution, designed meticulously to deliver outstanding performance and scalability across various dimensions like data volume, user concurrency, and query complexity, while also being cost-effective compared to other options available in the market. This adaptable platform supports deployment both on-premises and across a variety of cloud environments such as AWS, Azure, and Google Cloud, facilitating a seamless transition or gradual migration of applications and data as per your specific timeline. One of the distinguishing features of Actian Avalanche is its exceptional price-performance ratio from the start, which negates the necessity for extensive database administration tuning and optimization strategies. When juxtaposed with other alternatives, users can either experience significantly improved performance for a similar expenditure or enjoy equivalent performance at a considerably reduced cost. For example, GigaOm's TPC-H industry standard benchmark highlights Avalanche's impressive 6x price-performance leverage over Snowflake, with even greater advantages noted when compared to various appliance vendors, thus making it an attractive option for businesses in search of an efficient data warehousing solution. Moreover, this capability empowers organizations to harness their data more effectively, ultimately fostering insights and driving innovation that can lead to competitive advantages in their respective markets. The combination of these features positions Actian Avalanche as a forward-thinking choice for modern data strategies.
Integrations Supported
Amazon S3
Apache Spark
Hadoop
Jupyter Notebook
KNIME Analytics Platform
Marketo
Microsoft Azure
Microsoft Power BI
NetSuite
Oracle Database
Integrations Supported
Amazon S3
Apache Spark
Hadoop
Jupyter Notebook
KNIME Analytics Platform
Marketo
Microsoft Azure
Microsoft Power BI
NetSuite
Oracle Database
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Stone Bond Technologies
Date Founded
2002
Company Location
United States
Company Website
stonebond.com
Company Facts
Organization Name
Actian
Date Founded
2005
Company Location
United States
Company Website
www.actian.com/analytic-database/avalanche/
Categories and Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Business Intelligence
Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
Categories and Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge