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What's New in Pentaho 7.0?

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Veröffentlicht am

Pedro Martins, Head of Implementation Kleyson Rios, Solutions Architect

Veröffentlicht in: Technologie
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What's New in Pentaho 7.0?

  1. 1. What’s New in Pentaho 7.0? Pedro Martins, Head of Implementation Kleyson Rios, Solutions Architect
  2. 2. Data and analytics users spend the majority of their time either preparing data for analysis or waiting for data to be prepared for them. According to the Gartner Market Guide for Self- Service Data Preparation Analytics…
  3. 3. Today’s data landscape is littered with disparate tools and disjointed processes. How do you get ahead with that? Disparate tools, disparate problems Business Business Analytics Data Prep ETL / Data Engineering IT
  4. 4. 7.0 is about unlocking the data divide between business and IT. Leveraging the Pentaho platform to drive the business with usable, accurate, and accessible analytics across the organization. Business Business Analytics Data Prep ETL / Data Engineering IT Bridging the gap between data preparation and analytics
  5. 5. Pentaho’s platform today A data integration and business analytics platform that can access, prepare, blend and analyze any structured or unstructured data.
  6. 6. 1. Alleviates disparate tools and complexity. Pentaho’s future: a platform that fully enables a healthy data ecosystem 2. Makes analytics accessible at any stage of the data pipeline. 3. On top of governance, security, big data ecosystem support, and the required foundations of a blended data world.
  7. 7. Analyze data anywhere in the data pipeline Pentaho 7.0 Bridging the gap between data preparation and analytics with a Visual Data Experience from anywhere in the data pipeline: • Bringing Analytics into Data Prep • Share Analytics during Data Prep • Reporting Enhancements On top of governance, security, and Big Data ecosystem support for a blended data world: • Spark • Metadata Injection • Hadoop Security • Support for Kafka, Avro, Parquet • Admin Simplification
  8. 8. A Visual Data Experience From Anywhere in The Data Pipeline Pentaho 7.0
  9. 9. Imagine if you were able to access analytics from anywhere within the data pipeline
  10. 10. Bringing analytics into data prep Visualize data in-flight, without switching in and out of tools
  11. 11. Bringing analytics into data prep Access to tables, visualizations, charts, graphs, or ad hoc analysis during data prep.
  12. 12. Identify missing or incorrect data during the data prep process. Bringing analytics into data prep
  13. 13. Publish data sources to the business, and get data to the business faster Bringing analytics into data prep
  14. 14. Shrinking the gap between data preparation & business analytics 2. Creates a more collaborative process between business and IT, shortening the cycle from data to analytics. 1. ETL developers and data prep staff can easily spot check analytics without switching in and out of tools.
  15. 15. The ability to spot check and visualize our data throughout its lifecycle allows for a much more informative and streamlined data- driven decision making process to create more reliability, while reducing costs. ” Meir Kornfield, Director, Product Management and Business Intelligence, Sears Holdings Corp. “ A Visual Data Experience in the words of Sears Holdings Corp.
  16. 16. Big Data Ecosystem Support for a Blended Data World Pentaho 7.0
  17. 17. 7.0 makes big data operational Operationalize High Performance Pipelines with Spark Integration Protect Data Assets with Expanded Hadoop Security Automate Onboarding with Enhanced Metadata Injection
  18. 18. Spark potential Potential and Growth • Faster processing than MapReduce • Drives real time & intelligent big data applications at scale Market Challenges • Skill barriers – Spark requires specialized developer skills • Somewhat lacking in enterprise maturity – memory management, multi user access, etc. • Effective integration with broader data architectures is challenging
  19. 19. Current state: Pentaho and Spark • Execute Spark applications in PDI jobs • Supports existing Java and Scala code from core Spark libraries
  20. 20. Intuitive coordination of high performance pipelines Challenge: Hard to manage multiple Spark applications and multiple programming languages AND operationalize them in data pipelines with full flexibility 7.0 Expands Spark Orchestration • Coordinate and schedule Spark applications for Horton and Cloudera • Operationalize streaming, machine learning, and core Spark techniques within jobs • Choice of programming language, incl. Python
  21. 21. Remove skill barriers to use Spark Challenge: Spark requires specialized developer skills. Need an easy way to integrate Spark data with other data processes. 7.0 Adds SQL on Spark Connectivity • PDI access to SQL on Spark for rapid data prep and queries – on Horton and Cloudera • Improves productivity by using existing IT data skill sets on Spark • Accelerates time to value in big data pipeline projects
  22. 22. More secure clusters, better big data governance, and reduced risk Challenge: Protect key enterprise big data assets against intrusion and reduce risk of security breaches Expanded Hadoop Security • Secure multi-user access to the cluster via updated Kerberos integration, enabling user level tracking by mapping PDI users to Hadoop users • Compatibility with Sentry to enforce user authorization rules governing access to specific Hadoop data assets KERBEROS
  23. 23. Accelerate data onboarding with Metadata Injection Read Transform Write Data Source Data TargetData SourceData SourceData SourceData SourceData SourceData SourceData SourceData Source x100 What happens when data sources proliferate? Example use cases: • Migrating 100+ tables between databases • Ingesting 100+ data sources into Hadoop • Allowing end users to onboard data themselves
  24. 24. Accelerate data onboarding with Metadata Injection Read Transform Write Data Source Data TargetData SourceData SourceData SourceData SourceData SourceData SourceData SourceData Source x100 Read Transform Write Read Transform Write Read Transform Write Read Transform Write Read Transform Write Read Transform Write Read Transform Write Read Transform Write X100??? Build more transformations?
  25. 25. DRIVE HUNDREDS OF JOBS WITH 1 TEMPLATE Accelerate data onboarding with Metadata Injection Read Transform Write Data Source Data TargetData SourceData SourceData SourceData SourceData SourceData SourceData SourceData Source x100 Pass metadata in at run time to generate jobs on the fly Reduced development time, cost, and risk
  26. 26. Rapidly automate and scale big data onboarding Challenge: IT teams spend too much time coding ingestion and processing jobs for a wide variety of big data sources Metadata Injection Expansion • Expands options for auto-generated data flows, by allowing metadata to be passed to a wider array of PDI steps at runtime • Increases IT productivity when building out many data migration and onboarding processes • Now works with 30+ additional PDI steps • Includes compatibility with Hadoop, Hbase, NoSQL, JSON, XML, and Analytic DB steps
  27. 27. Steps Newly Enabled for Metadata Injection
  28. 28. Simplified configuration, deployment and administration of Pentaho Pentaho 7.0 reduces time to insights by making it faster and easier to configure, deploy and manage DI and BI services within development to production environments used to support the data lifecycle with no licensing impact Configure and Deploy Faster Simplify Administration
  29. 29. Pentaho 7.0 in Action Use Case: Retail bank needs to reduce costs and risk related to credit card fraud with a repeatable business process • Orchestrate workflow across components and integrate data in one end-to-end pipeline • Fewer tools and fewer new skills needed • Differentiated solution in the market for visual inspection of data at any step in the prep process • Data prep cycle time, time to insight accelerated Coordinate fraud model creation on Spark Ingest new transactions to Hadoop via Kafka Access modeled data for analysis via SQL on Spark Visually inspect data set for quality, completeness Collaboratively share results with the business
  30. 30. DEMO
  31. 31. No other platform lets IT and the business collaborate in this way, at such an early stage in the process. ” - Adrian Bridgwater, TechTarget “ Analysts & Press on Pentaho 7.0: So this looks to be a major enhancement which is really setting out the Pentaho stall as a BI vendor of choice at the Enterprise level with integrated capability which is easier to use and more powerful out of the box than the comparable offerings in the marketplace which are still reliant on skilled technicians to unite and enact the solutions. ” - David Norris, Bloor Research “ – Bev Terrell, SiliconANGLE As Hadoop can be a challenge around security, Pentaho is expanding its Hadoop data security integration to promote better Big Data governance, protecting clusters from intruders. ” “
  32. 32. Questions?
  33. 33. Thank You

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