Db2 Labs Agenda
Increase Availability and Reduce Downtime with the IBM Db2 Advanced Recovery Feature
Monday, 8:30 AM - 10:10 AM | Lab 21 | Session ID: 5688A
The IBM Db2 Advanced Recovery Feature combines three Db2 tools for advanced database backup, recovery and data extraction. These tools help improve data availability, mitigate risk and accelerate crucial administrative tasks. The three tools in the bundle we will talk about are DB2 Recovery Expert (granular recovery and log analysis features), Optim High Performance Unload (fast unload from database or backup) and Db2 Merge Backup (helps create more efficient backup strategies). Having these tools in your shop will help you do more and save money by helping to reduce application downtime and meeting service level agreements.
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Integrating Relational Data with Hadoop and Spark
Monday, 8:30 AM - 10:10 AM | Lab 10 | Session ID: 4636A
Hadoop systems are becoming more popular for storing and scalable processing of all kinds of data. At the same time, the desire to analyze these data in Hadoop efficiently with SQL is increasing. This lab shows how this can be achieved with IBM Big SQL. In addition, there is a need for more complex analysis and advanced analytics like machine learning with these data stored in Hadoop and relational database systems. Spark is a framework that is particularly well suited to this task. In this lab, we will show how processing in Spark can be integrated very easily with Big SQL and IBM Db2 Warehouse.
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IBM Db2 Analytics Accelerator: Modern Application Acceleration
Monday, 12:30 PM - 2:10 PM | Lab 21 | Session ID: 1288A
The IBM Db2 Analytics Accelerator (IDAA) brings revolutionary query performance to IBM Db2 for z/OS for select queries with great cost and performance characteristics. IDAA is deeply integrated with Db2 11 and 12 to combine the best of both IBM Z and PureData technologies and deliver unparalleled, mixed-workload performance to Db2 applications transparently. Acceleration of Db2 queries transparently on the IBM Integrated Analytics System is the next-generation offering that provides many benefits. This hands-on lab dives into new functions such as HTAP, Federation and also IBM Data Server Manager for IDAA.
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Advanced Analytics in IBM Db2 Warehouse
Monday, 2:30 PM - 4:10 PM | Lab 10 | Session ID: 4820A
IBM Db2 Warehouse combines the capabilities of a database system optimized for analytical applications such as Db2 with the ability to perform complex evaluations such as machine learning directly in the database, as well as simple integration with a cluster computing framework such as Apache Spark. This lab shows how developers can perform advanced analytics with data stored in Db2 Warehouse. Attendees will learn: 1) Creating fast and scalable solutions with Db2 Warehouse; 2) Using Spark to create applications; 3) Implementing data science/machine learning algorithms; 4) Using R and Python with Db2 Warehouse; and 5) Integration of IBM Data Science Experience in Db2 Warehouse.
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Unify Your IBM Db2 Warehouse with Hortonworks Data Platform to Enhance Analytical Insights
Monday, 2:30 PM - 4:10 PM | Lab 21 | Session ID: 1221A
Accelerate your enterprise's data-driven decisions by taking advantage of the partnership between IBM's Big SQL hybrid SQL engine and Hortonworks' Apache Hadoop ecosystem. Using IBM Fluid Query to limit data movement for blistering-fast performance, attendees will learn how to easily marry data between their IBM Db2 Warehouse private cloud and Hortonworks Data Platform. Cognos Analytics will be used to visualize query federation between the two platforms.
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Exploring Options to Move Your Data Warehouse to IBM's Software-Defined Private Cloud Platform
Tuesday, 10:30 AM - 12:10 PM | Lab 21 | Session ID: 1209A
IBM Db2 Warehouse is a software-defined environment that allows you to create a data warehouse behind your company's firewall, while simultaneously providing cloud-like scalability and appliance-like simplicity. This lab will first introduce how to migrate from traditional database platforms like Db2 and PureData System for Analytics to the IBM Db2 Warehouse. Next, attendees will get hands-on experience migrating database objects to the IBM Db2 Warehouse. Finally, various options to transfer data will be explored, such as via Db2 Support Tools, built-in commands, and the web console UI.
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Methods of Loading Data into IBM Db2 Data Warehouse on Cloud
Tuesday, 10:30 AM - 12:10 PM | Lab 18 | Session ID: 4128A
IBM Db2 Warehouse on Cloud is a fully-managed, enterprise-class, cloud data warehouse service. You can load data from a variety of sources into IBM Db2 Warehouse on Cloud. This lab will demonstrate a range of data loading techniques, like data loading from local files or local compress files or from other clouds like S3; and loading using ETL tools, REST APIs, dashboard console, on-premise databases or any heterogeneous sources like non-IBM data sources or Twitter data or from public datasets. After completing this lab user can identify data volume and nature of data (structured, semi-structured, and unstructured) and apply right techniques to load data quickly and easily into IBM Db2 Warehouse on Cloud.
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Wednesday, 12:30 PM - 2:10 PM | Lab 21 | Session ID: 5096A
This year marks an inflection point in the evolution of IBM Db2 Analytics Accelerator, with an exciting redesign of the system’s hardware and software stack. This next-generation technology brings a state-of-the-art, in-memory analytical engine to the mainframe. The Accelerator hardware is now based on the latest generation of IBM Power Systems and IBM Flash storage, and the software is based on Docker and IBM's premier columnar in-memory analytical engine—Db2 with BLU Acceleration. Join this hands-on lab to learn how the new generation compares to the current, Netezza-based Accelerator, how you can migrate from one to another and how both can coexist.
Wednesday, 2:30 PM - 4:10 PM | Lab 8 | Session ID: 4636B
Hadoop systems are becoming more popular for storing and scalable processing of all kinds of data. At the same time, the desire to analyze these data in Hadoop efficiently with SQL is increasing. This lab shows how this can be achieved with IBM Big SQL. In addition, there is a need for more complex analysis and advanced analytics like machine learning with these data stored in Hadoop and relational database systems. Spark is a framework that is particularly well suited to this task. In this lab, we will show how processing in Spark can be integrated very easily with Big SQL and IBM Db2 Warehouse.
Thursday, 8:30 AM - 10:10 AM | Lab 21 | Session ID: 6415A
Learn how to use IBM Db2 Event Store Developer Edition through Scala and Python Notebooks. The hands-on exercise will share an example of connecting to Event Store from an external application as well. The exercise will demonstrate how to perform a fast ingestion of data into Event Store and execute Spark queries against Event Store.