What is DataOps? Data Lineage for DataOps. How can MANTA help? Case study DataOps. DataOps implementation. E-books for free. Visit us at https://getmanta.com/

1. Enabling
DataOps with
Unified Data
Lineage

2. • Agile development, DevOps, and statistical
process controls
• Used by analytic and data teams,
to improve the quality and reduce the cycle time
of data analytics
• DataOps applies to the entire data lifecycle from
data preparation to reporting
What is DataOps

3. How Can MANTA Help
Shorten releases and deliver more often
Manual impact analysis is costly and time consuming.
Reduce the risk of future incidents
And minimize the downtime of the environment.
Shorter incident resolution
Quickly find which part of data pipeline was broken.

4. DataOps with MANTA
Fully mapped data pipeline accelerates debugging
Comprehensive APIs for launching lineage “on
demand” for selected assets
Complete lineage reporting improves communication
between teams
Instant lineage validation to support agile analytics
development

5. Problem:
One of MANTA’s customers, a European financial institution, had
gathered and been processing over a million algorithms of finance-
related logic in their data warehouse. This huge data warehouse
environment turned out to be a major obstacle to the Agile approach
that the organization had adopted.
Their plan to release weekly updates and deliver more
features with data analytics was sabotaged by the DataOps
team’s limited understanding of the environment. Every release
was flawed with
numerous issues, and manually figuring out what had caused the issues
was nearly impossible, not to mention preventing similar and other
issues in future releases.
Case Study DataOps

6. Solution:
To adapt the Agile approach and enable frequent, successful
releases, it was crucial for the DataOps team to immediately
understand data dependencies so they could assess the impacts of
planned changes before releases were implemented.
MANTA was implemented in their Teradata-based warehouse. This
allowed them to map their entire data pipeline within a few days,
facilitating frequent, fail-proof releases
Case Study DataOps

7. Result:
Mapping the environment helped the customer instantly spot the issues
that had caused the problems with the releases that had been launched
before implementing MANTA.
After mapping the entire data pipeline and making lineage an integral
part of every release, the Agile approach could be used, which
significantly shortened development release cycles and automated
the impact analysis process that now allows them to act proactively,
minimizing the risk of broken releases in the production environment.
Case Study DataOps

8. Need more info?
Read how MANTA
helped a customer
facilitate frequent
changes, releases, and
continuous deployment
in a large environment of
over 1,000,000
algorithms.
Learn more about
MANTA’s Revisions
(time slicing) feature,
and discover how
comparing historical
revisions will help you
achieve a holistic view
of your data landscape
and support DataOps
implementation.
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