Getting the best AI models and analytics results mean quickly and efficiently delivering data to the cloud with accuracy, consistency, and context. But when you must connect legacy systems like mainframe and IBM i to the cloud, your project can become expensive, time-consuming, and reliant on highly specialized skillsets. So much for speed and efficiency! View this on-demand webinar to explore how data from mainframe and IBM i can deliver the trusted data required for advanced analytics and artificial intelligence within Databrick’s Unified Analytics Platform.

1. Accelerate Innovation:
Databricks and Legacy Data
Precisely and Databricks Partnership Overview
Ashwin Ramachandran | Senior Product Manager

2. Housekeeping
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Recording and slides
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3. Precisely: Accelerate Innovation with Databricks and Legacy Data
Data is the hardest part of any data project
Disparate and unreliable
data - major contributing
factors to analytics,
machine learning, and AI
project failures
Inconsistent adoption of
various tools and third-
party embedded
integration utilities
Legacy data is not
readily compatible with
cloud platforms and
cloud data warehouses

4. Simplify
your
process
Consider
your
architecture
Develop
your
strategy
Understand
your gaps
Precisely: Accelerate Innovation with Databricks and Legacy Data

5. Don’t leave legacy
data behind
• How fast can you integrate
legacy systems?
• How will you understand
mainframe or IBM i data?
• How can you best optimize for
extreme data volumes?
Precisely: Accelerate Innovation with Databricks and Legacy Data5

6. Precisely: Accelerate Innovation with Databricks and Legacy Data
Future-proof your environment
Quickly and easily add sources or targets
Design once, deploy anywhere approach
Guaranteed data delivery
True real-time delivery
✔
✔
✔
✔

7. Joint value: Precisely & Databricks
• Experts in liberating data from
legacy data sources
• Build visual streaming data
pipelines
• Modernize ETL processes and
scale with high-performance
engine
• Capture changes to data in
real-time
• 10-100x faster than Open
Source Spark with Delta as the
core engine for PB scale
processing
• Lowest TCO through auto-
scaling and auto-configuration
capabilities
• Unified, collaborative
experience for data engineers
& data scientists on one
platform
Precisely: Accelerate Innovation with Databricks and Legacy Data

8. Precisely: Accelerate Innovation with Databricks and Legacy Data
Get data from legacy sources into the data lakehouse!
Want your data from legacy, mainframe and IBM i is loaded as-is to the cloud?
• Easily create an exact bit-for-bit copy of
mainframe and IBM i data on the Cloud
• Work with that data in Spark – native Spark
integration
• Map data directly to copybook in Spark
• End-to-end managed approach for
offloading data
• Directly access and understand VSAM,
mainframe fixed and variable files, and
Db2 data
• Take a design once, deploy anywhere
approach to data integration
• Transform data on the fly – no staging
• Import hundreds or Db2 tables to your
data lakehouse with a few mouse clicks
• Distributed ETL on Databricks
• High-performance, self-tuning sorts,
joins, aggregation, merges, and look-
ups optimized to run natively in the
Databricks run-time
• Dynamically optimize loads for extreme
data volumes
• Break down data silos in minutes

9. Precisely: Accelerate Innovation with Databricks and Legacy Data
Connect and Databricks
Mainframe
,
IBM i
Relational
databases,
EDW, DBMS
Flat files,
XML, JSON
Ingest
&
Stream
Data
Integrate,
Prepare,
Load,
Cleanse,
Transform
Unified Data Analytics Platform
Reporting and BI
Deliver
Data
Data Sources
Hadoop,
HDFS
Connect’s ETL capabilities
and Databricks eliminate data
silos across your business