Modern Analytics from SAP (Part 1)

Author – Anooj Behanan – Practice Director – Analytics

Digital transformation or rather digitisation has forced organisations to rethink business models, value propositions to their customers and ways and means to both create and capture value to further their competitive advantage. The advent and democratisation of digital technologies such as the Internet of Things, AI, Machine Learning, Blockchain, Virtual Reality among others have helped fast-track this digitisation process for most companies.

Role of Data & Insights

Underpinning this digital platform, of course, is the need to have a secure, robust and agile Data and Insights foundation. At an abstract level, the requirements to construct such a layer are –
• Means to integrate and federate data (structured and unstructured) of varying degrees of volume from a multitude of sources both internal and external to the enterprise
• Ways to transform and harmonise this data real-time while ensuring quality and security
• Moreover, be smart at deriving meaningful insights, predict events and also prescribe specific actions, i.e., be insights driven as opposed to just being data-driven

To allow this, today’s business managers need the mind shift to consider ‘Data’ as ‘Assets’ that not just aids operational efficiencies but also see them as levers to drive out-of-the-box thinking in strategic decision making that makes a truly digital enterprise.

SAP’s Intelligent Enterprise

SAP’s ‘Intelligent Enterprise’ brings together the digital platform, technologies and its Intelligent ERP Suite under one umbrella to maximise the value of data assets and achieve desired outcomes faster. Data and Analytics are right at the centre of this enterprise.

 

The proliferation of in-memory computing, big data, cloud and advanced analytics technologies such as predictive have led to key innovations in SAP’s Analytics product portfolio. Staying in line with the above-mentioned role of data & insights, they can be broadly categorised as a) Embedded Analytics b) Enterprise Data Warehouse and Strategic Insights and c) Cloud Analytics.

Embedded Analytics

Before HANA, simple operational reporting out of SAP ECC was run using SAP Query and ABAP reports whereas SAP BW (Business Warehouse) or a separate data warehouse had to be considered for complex and data-intense reporting requirements in line with the best practices at the time to keep OLTP and OLAP processing separate. Needless to say, this came with the need to replicate (in regular batches), transform, aggregate and reconcile data sets between multiple data stores.

The advent of HANA and in-memory computing made real-time reporting possible on OLTP systems with the bulk of data aggregation possible on the fly eliminating the need for data redundancies.  SAP leveraged HANA to build S/4HANA for both cloud and on-premise to form the digital core of its Intelligent Suite alongside SAP SuccessFactors (People Engagement), C/4HANA (Customer experience) and others.

S/4HANA enables analytics on live transactional data allowing quick operational decision-making. The data models are made available via pre-delivered CDS views (core data services) that are fully integrated with the ABAP development lifecycle and visualised using SAP Fiori Apps and SAP Analytics Cloud. SAP has further extended this by embedding analytics into transactions that function based on the user context and specific role. An example – while creating a sales order, using embedded analytics, S/4HANA is now able to identify the closest warehouse with availability, project customer run rate based on historical orders and also identify cross-sell and up-sell opportunities before completing the entry.

With SuccessFactors soon to be available on HANA, its operational reporting will be replaced with the embedded SAP Analytics Cloud variant. Other business apps are to follow a similar direction based on indications from SAP’s product roadmap.

I will be presenting at our forthcoming What’s Next for SAP BW and Analytics session in October exploring answers to pertinent questions including:

– Where operational analytics needs are not fully met by pre-defined models/apps, what extension tools & capabilities are available?
– How can operational analytics using data across SAP and non-SAP transactional applications both cloud and on-premise be made possible?

Join itelligence at the What’s Next for #SAP BW and Analytics session to find answers to the questions stated above, see live demos of embedded analytics, BW/4HANA and SAP Analytics Cloud, discuss SAP Analytics strategy & architecture options and much more.

To see the second part of this blog looking at areas such as the Enterprise Data Warehouse, Strategic Insights and Cloud Analytics please visit here

 

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