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Ratings and Reviews 0 Ratings
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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.
What is Oracle Big Data Discovery?
Oracle Big Data Discovery stands out as a highly visual and intuitive tool that leverages Hadoop's capabilities, transforming raw data into actionable insights for businesses in mere minutes, thus negating the need for extensive tool mastery or reliance on specialized experts. This innovative solution allows users to easily pinpoint relevant data sets within Hadoop, quickly explore the data to understand its significance, improve its quality through enhancement and refinement, analyze it for fresh insights, and disseminate findings while effortlessly reintegrating into Hadoop for organization-wide applications. By establishing BDD as the foundational element of your data lab, your organization can foster a unified environment for examining and navigating diverse data sources within Hadoop, which streamlines the development of projects and applications. Unlike traditional analytics platforms, BDD opens the door for a wider audience to interact with big data, drastically cutting down the duration required for data loading and updates, hence enabling teams to focus on significant data analysis and exploration. This transition not only boosts productivity but also democratizes data access, enabling a greater number of individuals to participate in data-driven decision-making processes, ultimately leading to improved outcomes for the organization. Furthermore, by empowering users across various skill levels, BDD cultivates a culture of collaboration and innovation in data utilization, fostering an environment where insights can be rapidly derived and acted upon.
What is Anatics?
Effectively transforming data and performing marketing analysis is vital for building confidence in marketing investments and enhancing returns on advertising spending. When unstructured data is poorly managed, it can undermine marketing decisions, making it imperative to efficiently extract, transform, and load your data to carry out marketing initiatives with certainty. Utilizing anaticsTM allows you to unify and centralize your marketing data for easier access and management. By loading, normalizing, and transforming your data meaningfully, you enable thorough analysis and performance tracking. Collecting, preparing, and analyzing all of your marketing information becomes a breeze, freeing you from the monotonous task of manually pulling data from multiple platforms. With automated data integration from over 400 sources, exporting your data to preferred locations becomes seamless. Storing your raw data in the cloud guarantees that you can retrieve it whenever necessary while strengthening your marketing strategies with dependable information. Focus on driving actionable growth instead of navigating the cumbersome process of managing countless spreadsheets and CSV files, which allows for a more effective resource allocation. By adopting this innovative approach to managing marketing data, you not only streamline processes but also create an environment where your business can truly flourish and adapt to changing market dynamics.
Integrations Supported
Altair Compose
Amazon Web Services (AWS)
Bing
Commvault Cloud
Expedia
Google Analytics
Google Business Profile
Hadoop
LinkedIn
Mailchimp
Integrations Supported
Altair Compose
Amazon Web Services (AWS)
Bing
Commvault Cloud
Expedia
Google Analytics
Google Business Profile
Hadoop
LinkedIn
Mailchimp
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
$500 per month
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
Oracle
Date Founded
1977
Company Location
United States
Company Website
www.oracle.com/middleware/technologies/big-data-discovery.html
Company Facts
Organization Name
Anatics
Company Location
United States
Company Website
anatics.com
Categories and Features
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Categories and Features
Customer Data Platforms (CDP)
Behavioral Analytics
Campaign Management
Customer Profiles
Customer Segmentation
Data Integration
Data Matching
GDPR Compliance
Personalization
Predictive Modeling
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Discovery
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Management Platforms (DMP)
Ad Network Integration
Analytics / ROI Tracking
Audience Targeting
Behavioral Analytics
CRM
Campaign Management
Competitive Analysis
Customer Journey Mapping
Data Capture / Transfer
Data Classification
Data Visualization