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So we have been putting Cart before the Horse – Taking data out of HANA landscape for reporting and analytics….

So we have been putting Cart before the Horse – Taking data out of HANA landscape for reporting and analytics….

It is the time to CORRECT it…

Typical data and analytics reference architecture will look like one below having key layers of Data Source, Ingestion, Data layer and consumption layer.

Typical%20reference%20architecture

Typical reference architecture

Recently I have seen a trend of having a big data or cloud solution along with HANA data platform in SAP data and analytics ecosystem. Initially purpose of this so call “Big data platform” was to cater to huge amount of low value high transaction data which could be harmonized and may be consolidated and merged with enterprise data (read HANA platform data) for reporting and analytics.

Something strange started happening recently, this “Big data platform”, lot of customer started extracting data from HANA and migrating to this platform and they are doing it primarily for below reasons:

  • Growing HANA data size and associated cost with HANA. (Is bringing in another data platform in only way to address this?)
  • Quick LOB kind of analytics on Cloud i.e. a particular part of business needs something quick and they end up putting this data on cloud and give access to that group. (Now this group has two access points to same data HANA reports and Big data platform BI, here starts the real game of redundancy, security and more importantly reconciliation)
  • They have already invested in “Big Data Platform” and struggling to show value, this is one of the ways to monetize? (Who cares of over cost of ownership with data extraction, data mapping, multiple reports, and multiple access points for business to access data, managing multiple vendors and their solution compatibility, building security layers etc.?)

While interacting with various stakeholders of multiple such projects (extracting SAP HANA data / ecosystem data and migrating to “Big data platform” and make sense of it), I have reached to conclusion that these are not straight forward projects as SAP data needs to be understood in business context of SAP process and SAP Ecosystem. Because of this, most of these projects could not achieve what they aspire to. What I have also understood is from TCO (Total cost of ownership) perspective also customers do not really benefit over longer term.

My humble suggestion to all stakeholders, who are executing or plan to execute similar projects, please take a step back and revisit – “Why did you decide to invest HANA in first place?”

SAP does provide options to optimize TCO and provide LOB specific data and reporting access that too on the cloud i.e. HANA Cloud & Data Lake.

HANA%20Cloud%20Data%20Lake%20Source%3ASAP

HANA Cloud Data Lake Source:SAP

With above architecture (HANA Cloud + Data Lake) following architecture options can be evaluated:

Option I Option II
HANA Cloud + Data Lake*+SAC (SAP Analytics Cloud) Data Warehouse Cloud
  • Real-Time Analytics
  • Complex Modeling capability
  • High Performance
  • Highly  Scalable leverage underlined HANA Cloud & HANA Data Lake
  • Data persistency + Virtualization ( consumption models)
  • Ability to leverage Native HANA capabilities
  • Highly Elastic
  • Mobility enablement
  • Future ready to leverage Advanced Analytics Models e.g. AI, ML etc.
  • Real-Time Analytics
  • Complex Modeling capability
  • High Performance
  • Highly  Scalable leverage underlined HANA Cloud & HANA Data Lake
  • Virtualization + Persistency (leveraging DWHC federation)
  • Additional Business Layer specifically meant for LOB Analytics (FI, HR, Sales etc.)
  • Highly Elastic
  • Mobility enablement
  • Future ready to leverage Advanced Analytics Models e.g. AI, ML etc.

Please do share what you are observing in your SAP Data and Analytics ecosystem and your views on adoption HANA Cloud & Data Lake.

(View are purely personal and not of my organization)

1 Comment
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  • Thank you for this Blog. I would like to add :

    Taking data out of SAP context to store it in other data lake you might run into :

    Losing the authorization profiles that are within SAP.
    Decontextualising the SAP data models by losing the Business view.
    Not being able to propagate the SAP business model to other non-SAP data.

    On the other hand, adopting a solution such as SAP HANA Cloud or SAP Data Warehouse Cloud would not cause the three problems described above.