Data Lakes: 8 Enterprise Data

Management Requirements

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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