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Instantly Convert Teradata ETL and EDW to
Spark On Cloud or On Premise
Hari Kodakalla
Director Big Data Strategy
Barry Tuthill
VP Field Operations
Agenda
The case for modernization
Where to get started
Our solution
A case study
Demo
Q&A
Our Mission
Enabling a unified, clear and present view
of your business.
Poll
Our speakers
Hari Kodakalla
Director Big Data Strategy
Barry Tuthill
VP Field Operations
The case for modernization
The case for modernization
Business readiness
The case for modernization
Business readiness
Technology readiness
The case for modernization
Business readiness
Technology readiness
Strategic readiness
The call for a modern architecture that can
provide a Unified Single Source of Truth.
Key features of a modern data architecture
Key features of a modern data architecture
Flexible
Key features of a modern data architecture
Cost efficient
Key features of a modern data architecture
Versatile
Key features of a modern data architecture
Secure
The journey from Teradata to a modern
data infrastructure
Key action items
Key action items
Select platform components
Key action items
Select platform components
Address cultural requirements
Key action items
Select platform components
Address cultural requirements
Minimize risks
The first stumbling blocks
The first stumbling blocks
Where do you start?
The first stumbling blocks
Where do you start?
Who will do all this transformation?
More open questions…
Potential sources of risk
Potential sources of risk
Overwhelming
Potential sources of risk
Overwhelming
Too complex
Potential sources of risk
Overwhelming
Too complex
Time consuming
Potential sources of risk
Overwhelming
Too complex
Time consuming
Limited expertise
These could all lead to strategy failures
and serious disruptions.
Poll Results
The strategy dilemma
Achieving the right balance
Migrating as is Total re-engineeringTransfer and transform
? ??
How can we help?
We can help move your Teradata warehouse
to where you want to be, on cloud, on premise,
or hybrid. Automagically.
We bring agility with automation
1
2
3
4
Assess
Transform
Validate
Execute
Automated vs. manual
Impetus
Automated
Workload
Transformation
Manual
Migration
Week
Assess
Assess
0 4 8 12 16 20 24 28 32 36 … 48 … 75
Transform
Validate
Execute
Migrate
Validate
Debug & Revalidate
Execute
A transformation engine that learns
SQL, PLSQL Spark SQL
Stored Procedures,
BTEQ
Teradata ETL
Hive QL
Spark Scala,
Java, Shell, Python,
NiFi/Sqoop,…
Workload
Transformation
Engine
The case of a US-based Fortune
Global 20 Telco…
What were their challenges?
Data volumes
Increasing costs
Complex code
What did they accomplish?
Transformed 20,000 production queries automatically to Spark SQL
Migrated historical and incremental data with SCD
Optimized query, script, and architecture for performance gains
What did they accomplish?
Teradata dependency diminished significantly
Process ETL rapidly on top of the data lake
Handle data growth of 100–200% per year
Enable massive new analytics capabilities
Demo
Q&A
Thank you
Visit us at www.impetus.com/transform

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Instantly convert Teradata ETL and EDW to Spark- Impetus webinar

Editor's Notes

  • #8: The case for modernization is driven from 3 distinct perspectives of readiness and the state that each organization sees itself in Business Readiness What are the key business needs from an Analytics perspective, are they being met . Are the goals well defined Does the current state adequately addressing the needs both current and future Are you at risk of not being able to support emerging near term and long term needs Technology Readiness Is there a aging technology risk for the prevailing tech stack of choice Are there any points of integrations difficult to maintain for a well integrated ecosystem / platform Are performance needs being met for current users Does the current platform capable of satisfying anticipated needs of analytical demand Strategic Readiness How is the balance between the platform strategy , tech adoption and day-2 day operations risk Can the current strategy whether anticipated demands without disruption
  • #9: The case for modernization is driven from 3 distinct perspectives of readiness and the state that each organization sees itself in Business Readiness What are the key business needs from an Analytics perspective, are they being met . Are the goals well defined Does the current state adequately addressing the needs both current and future Are you at risk of not being able to support emerging near term and long term needs Technology Readiness Is there a aging technology risk for the prevailing tech stack of choice Are there any points of integrations difficult to maintain for a well integrated ecosystem / platform Are performance needs being met for current users Does the current platform capable of satisfying anticipated needs of analytical demand Strategic Readiness How is the balance between the platform strategy , tech adoption and day-2 day operations risk Can the current strategy whether anticipated demands without disruption
  • #10: The case for modernization is driven from 3 distinct perspectives of readiness and the state that each organization sees itself in Business Readiness What are the key business needs from an Analytics perspective, are they being met . Are the goals well defined Does the current state adequately addressing the needs both current and future Are you at risk of not being able to support emerging near term and long term needs Technology Readiness Is there a aging technology risk for the prevailing tech stack of choice Are there any points of integrations difficult to maintain for a well integrated ecosystem / platform Are performance needs being met for current users Does the current platform capable of satisfying anticipated needs of analytical demand Strategic Readiness How is the balance between the platform strategy , tech adoption and day-2 day operations risk Can the current strategy whether anticipated demands without disruption
  • #11: The case for modernization is driven from 3 distinct perspectives of readiness and the state that each organization sees itself in Business Readiness What are the key business needs from an Analytics perspective, are they being met . Are the goals well defined Does the current state adequately addressing the needs both current and future Are you at risk of not being able to support emerging near term and long term needs Technology Readiness Is there a aging technology risk for the prevailing tech stack of choice Are there any points of integrations difficult to maintain for a well integrated ecosystem / platform Are performance needs being met for current users Does the current platform capable of satisfying anticipated needs of analytical demand Strategic Readiness How is the balance between the platform strategy , tech adoption and day-2 day operations risk Can the current strategy whether anticipated demands without disruption
  • #12: As one examines the answers to some of the key questions raised from the 3 dimensions of readiness enterprises start quickly realizing the imminent risks and expose the need for a modern architecture to mitigate the challenges . Which in turn triggers a flurry of activities across the organizations that potentially could span over a couple years to engage in this transformational journey that we are here to talk about This journey of transformation and innovation that demands the availability of a single source of truth and a modern data platform capable of breaking down barriers and impediments in the organizations way to realize the sophistication they demand and excel in their sphere of business We can see that in the industry more today then ever before , Where Gartner has quoted that more than 80% of enterprises having launched modernization initiatives. All of these initiatives have a single goal in mind---to create the data driven enterprise of the future based on a single source of truth.     What are “must haves” for such an architecture? The key characteristics and drivers of such an architecture are centered around:   There are a number of fundamental capabilities that need to be present. (Could mention a few without elaborating much on any one). {PICK A FEW: Flexibility – In accommodating new forms of use cases with the changing business use cases, elastic architecture that adapts to changing data processing requirements  Efficiency –Responding in real-time is critical to the customer experience Customer -centricity Automated Resilient Cost - Cost becomes an important yard stick in choosing the  Advanced Analytics – This is needed to derive the insights on which business can take decisions   Strategic value – This new architecture should be in line with the enterprise data strategy to be ‘cloud ready’ Technological value – It should have the relevant technology proposition to take the enterprise to the next level}   Independence from vendor lock-in for agile innovation – Not getting locked in vendor’s platform is very important. Secure   But one thing is clear. We MUST have access to all of the enterprise data. And for Teradata users, much of that is held inside the Teradata warehouse. How can we swiftly re-commission this data onto the modern data architecture?   Impetus has been constantly working with customers and partners alike to help them identify the various components that enable this modern architecture, in fact Dhiren can you provide some insights into what you are also observing as a Product Manager as you bring these capabilities to our specific offerings.
  • #27: Consider your potential sources of risk: the project can be…
  • #28: Consider your potential sources of risk: the project can be…
  • #29: Consider your potential sources of risk: the project can be…
  • #30: Consider your potential sources of risk: the project can be…
  • #31: Consider your potential sources of risk: the project can be…
  • #43: This is what was accomplished…
  • #44: …facilitating this future. Teradata dependency diminished significantly -> Saving millions of dollars on recurring licensing cost