Purpose-built for data specialists to deliver rapid, real-time business insights with the enterprise-grade security and governance that IT demands
– CDP Data Engineering
– CDP Operational Database
– CDP Data Visualization
Cloudera (NYSE: CLDR), the enterprise data cloud company, today announced new and upcoming enterprise data cloud services on Cloudera Data Platform (CDP): CDP Data Engineering; CDP Operational Database; and CDP Data Visualization. The new services are analytic experiences designed specifically for data specialists and, unlike general purpose services that require add-ons for critical capabilities like workflow automation, job prioritization, and performance tuning, include these key capabilities to help data engineers, data analysts, and data scientists work smarter and faster. CDP enterprise data cloud services are purpose-built to enable data specialists to confidently navigate the storm of exponential data growth and siloed data analytics operating across multiple public and private clouds.
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Every business is facing a perfect storm of radical change, supercharged by the impact of a global pandemic. Everything from face-to-face meetings to buying groceries has gone digital almost overnight. As a result, organizations are generating more data than ever, at every point of business. There are more digital transactions to track and monitor. Every engagement with coworkers, customers, and partners is virtual. With this deluge of data flooding every enterprise, Cloudera believes this onslaught offers an opportunity to make better business decisions, faster. The Cloudera Data Platform can leverage virtually unlimited quantities and varieties of data, from any point in the data lifecycle, to power better decision making.
Data lifecycle integration is what enables data engineers, data analysts and data scientists to work on the same data securely and efficiently, no matter where that data may reside or where the analytics run. CDP not only helps to improve individual data specialist productivity, it also helps data teams work better together, through its unique hybrid data architecture that integrates analytic experiences across the data lifecycle and across public and private clouds. Effectively managing and securing data collection, enrichment, analysis, experimentation and analytics visualization is fundamental to navigating the data storm. The result is data heroes can collaborate better and more rapidly deliver data-driven use cases, like predictive maintenance and customer 360, that the business requires to compete and serve customers better.
“Our customers understand the importance of the data lifecycle to infuse data-driven decision making throughout their business, traditionally integrating data clusters for NiFi, Kafka, Spark, Impala, Hive, HBase and more,” said Arun Murthy, chief product officer, Cloudera. “That still works for data experts – architects and developers – who can use our data lifecycle cluster service – CDP Data Hub. Now with CDP’s analytic experiences, data specialists like engineers, analysts and scientists get exactly what they need to work better, without having to understand or manage clusters, with built-in security and governance across the data lifecycle to make it easy for IT. It’s one enterprise data cloud that works for everyone.”
CDP Data Engineering
CDP Data Engineering is a powerful Apache Spark service on Kubernetes and includes key productivity enhancing capabilities typically not available with basic data engineering services:
- Visual GUI-based monitoring, troubleshooting and performance tuning for faster debugging and problem resolution
- Native Apache Airflow and robust APIs for orchestrating and automating job scheduling and delivering complex data pipelines anywhere
- Resource isolation and centralized GUI-based job management
- CDP data lifecycle integration and SDX security and governance
“The role of data engineering in preparation for data science is instrumental for operationalization,” said Stewart Bond, Research Director of IDC’s Data Integration and Intelligence Software service. “There’s a common problem of ML models not getting into production, in part due to challenges associated with automating data engineering pipelines as organizations struggle to connect the dots. There’s value in an integrated platform that can bring it all together.”
Preparing data for analysis and production use cases across the data lifecycle is critical for transforming data into business value. CDP Data Engineering is a purpose-built data engineering service to accelerate enterprise data pipelines from collection and enrichment to insight, at scale.
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CDP Operational Database
As businesses continue to generate large volumes of structured and unstructured data, developers are tasked with building applications that democratize data access, enable actions in real-time and are integral to business operations and revenue generation. Unlike general purpose database services, CDP Operational Database is a high-performance NoSQL database service that provides unparalleled scale and performance for business critical operational applications, offering:
- Evolutionary schema support to leverage the power of data while preserving flexibility in application design by allowing changes to underlying data models without having to make changes to the application
- Auto-scaling based on the workload utilization of the cluster to optimize infrastructure utilization and cost
- Multi-modal client access with NoSQL key-value using HBase APIs and relational SQL with JDBC, making CDP Operational Database accessible to developers who are used to building applications that use MySQL, Postgres, etc.
- CDP data lifecycle integration and SDX security and governance
CDP Data Visualization
Analysts and data science teams need to be able to share and explain analytical results in a way that business stakeholders can quickly understand and operationalize. Business users also need the ability to discover and curate their own visualizations from data and predictive models in a self-service manner. CDP Data Visualization simplifies the curation of rich, visual dashboards, reports and charts to provide agile analytical insight in the language of business, democratizing access to data and analytics across the organization at scale:
- Technical teams can rapidly share analysis and machine learning models using drag and drop custom interactive applications.
- Business teams and decision makers can consume data insights and make trusted, well informed business decisions.
- All teams benefit from fast data exploration using AI-powered natural language search and visual recommendations.
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