The document outlines eight essential requirements for enterprise data management in data lakes, including storage capabilities, data ingestion tools, and data discovery methods. It emphasizes the importance of modern integrations for streaming data, effective management of metadata and governance, and secure gateways to the data lake. Additionally, it encourages enterprises to avoid outdated integration solutions as they develop their data lake strategies.

1. Data Lakes:
8 Enterprise Data
Management
Requirements

2. 2
Requirement #1: Storage and Data Formats
A key concept of the data
lake is the ability to
reliably store a large
amount of data. Such
data volumes are
typically much larger than
what can be handled in
traditional relational
databases, or much
larger than what can be
handled in a cost-
effective manner.

3. 3
Requirement #2: Ingest and Delivery
Just like with data
endpoints and data
formats, the right
commercial tools can
help describe the lake
data and surface the
schemas to the end
users more readily.

4. 4
Requirement #3: Discovery and Preparation
Commercial offerings
in the data discovery
and basic data
preparation space
offer web-based
interfaces (although
some are basic on-
prem tools for so-
called "data blending")
for investigating raw
data and then devising
strategies for
cleansing and pulling
out relevant data.

5. 5
Requirement #4: Transformations and Analytics
In the data lake,
we see three types
of transformations
and analytics:
simple
transformations,
analytics queries
and ad-hoc
computation.

6. 6
Requirement #5: Streaming
Modern integration
tools can help feed
Kafka, process Kafka
data in a streaming
fashion, and also feed
a data lake with
filtered and
aggregated data.

7. 7
Requirement #6: Metadata and Governance
Look to see
commercial data
integration solution
providers develop
new ways to
manage metadata
and governance in
the enterprise data
lake.

8. 8
Requirement #7: Scheduling and Workflow
Commercial data
integration tools
provide high-level
interfaces to
scheduling and
workflow, making
such tasks more
accessible to a wider
range of IT
professionals.

9. 9
Requirement #8: Security
Commercial
products can serve
as a gateway to the
data lake and
provide a good
amount of security
functionality that can
help enterprises
meet their security
requirements in the
short term, then
adopt standardized
mechanisms as they
become available.

10. 10
Don't settle for
same old, same
old data
integration as you
build your vision
for an enterprise
data lake to power
next-generation
analytics and
insights.

11. 11
Powering the Enterprise Data Lake with Modern Integration
SnapLogic.com/bigdata

12. 12
SnapLogic.com
Don’t let you legacy integration
solution be your legacy.
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