SAP HANA Data Strategy

Overview

As database and business analytics professionals we have always struggled with implementing the business’s conceptual data model and analytics strategy given the limitations of traditional database technologies. We understand the data and the many attributes that allow us to view the data from many angles, but the traditional database technologies did not allow us to create very wide tables and limited the number of ways we could access the data. These limitations then drove the models to have multiple copies of data summarized for specific use cases. All of these traditional database limitations lead us to create very complex models for solving quite straight forward problems. The complexity of the data models then created limited flexibility and tremendous latency.

I would equate this to an artist or a designer that have a big idea, but they are limited to using eight and half by eleven pieces of paper and then only allowed to show particular segments of their design like putting a limited number of well-designed empty toilet paper rolls on their designs for viewing. They end up spending most of their time taping the pieces of paper together or moving the toilet rolls around and spend a small fraction of their time actually working on the art or design.

The beauty of working on a SAP HANA Data Strategy is it is like giving the same artist or designer a high-tech piece of paper that will automatically expand to any width or any length and allowing viewers to see everything all at once. In this way they can spend their entire time getting their ideas on the paper and knowing that the consumer of the art will be able to view the entire piece from any point of view or any angle they wish.

In this ongoing series of Blogs and videos we will be covering all aspects of SAP HANA Data Strategy including:

◈ SAP HANA Virtual Data Modeling

◈ SAP HANA Data Ingestion

◈ SAP HANA Data Architecture

◈ SAP HANA Data Consumption

We will also continuously add content to cover these concepts deeper and wider than ever before and we will strive to keep the content current by covering new features as releases of SAP HANA evolve. Throughout this series you will learn how easy it is to actually implement these concepts and discover what SAP means by “Run Simple”.

HANA Virtual Data Modeling

Product: SAP HANA 2.0 SP04

Feature: HANA Virtual Data Modeling

Why talk about HANA Virtual Data Modeling and why now???

◈ It is what is driving real-time analytics while lowering the total cost of ownership (TCO) of the solution

◈ Customers need a deeper understanding of the newer HANA HDI features

◈ There are no comprehensive HANA virtual modeling sources

◈ Virtual modeling is at the heart of HANA Intelligent Digital Business Platform solution

Driving real-time analytics while lowering the total cost of ownership (TCO) of the solution

Once customers begin to adopt all of the HANA virtual data modeling features, they will drive out all of the latency from their traditional approaches to analytics, creating a true real-time environment and at the same time significantly lower the TCO of the solution by eliminating the need for tradition ETL, change data capture, data streaming and modeling infrastructures. The real-time aspect of this solution means that as soon as an event (order, meter reading, phone call) occurs anywhere in any system in a company’s enterprise, the HANA Intelligent Digital Business Platform will analyze and deliver insight based on that event to the business.

Customers need a deeper understanding of the HANA HDI feature

With many customers planning their HANA 1.0 to HANA 2.0 upgrades, some are uninformed on the topic of the newer HANA Deployment Infrastructure (HDI). They need to understand that support for the original HANA schemas and calculation views now referred to as “HANA Classic” are still supported in HANA 2.0 SPS4 and the next release SPS05. They also need a better understanding of exactly what HDI is, so they will have less fear about eventually migrating their existing DB artifacts to HDI and developing new DB artifacts in HDI to take advantage of the newer HANA features.

There are no comprehensive HANA virtual modeling sources

HANA data modeling is specifically referring to the modeling of any HANA artifacts that design:

◈ Data,
◈ Data access, and
◈ Data ingestion into HANA.

Data artifacts such as tables and HANA CDS views. Data access artifacts such as database views, calculation views, or stored procedures. As well as HANA Enterprise Information Management (EIM) and HANA streaming artifacts such as Smart Data Access (SDA) virtual tables and Smart Data Integration (SDI) flow-graphs and SDI replication tasks and Smart Data Streaming (SDS) streaming jobs.

Many of these topics have been discussed but very seldom if ever are they all covered as the single comprehensive solution which the HANA Intelligent Digital Business Platform solution provides.

We are not covering any HANA application modeling such as JAVA, SAP UI5 and Fiori GUI front ends.

Virtual modeling is at the heart of HANA

HANA virtual data modeling as it is referred to here, is primarily HANA virtual calculation view (CV) modeling. This database modeling is at the heart of the HANA real-time data analytics. It is used on many layers of the data access structure performing tasks such as:

◈ User created self-service reporting,
◈ Business analytics,
◈ Creation of business objects from standard application tables, and
◈ Enterprise wide harmonization of data from different back-end silos

The fact that all these layers are virtual models is what gives HANA the ability to deliver real-time business analytics without incurring the tremendous latency created by traditional extract transform and load (ETL) processes.

HANA Data Ingestion

Product: SAP HANA 2.0 SP04

Feature: HANA EIM (SDA/SDI/SDQ), HANA SDS

HANA Data Ingestion allows for:

◈ Virtual data access,
◈ Batch data movement, and
◈ Real-time data movement

HANA data ingestion includes many ways of accessing data virtually which allows simple and immediate access to data across the entire enterprise and well as third party data. HANA data ingestion also includes the ability to batch part or all of a data set into the HANA data architecture for temporary or permanent access. HANA data ingestion also includes real-time data movement from database transactions, applications and streaming data.

HANA Data Architecture

Product: SAP HANA 2.0 SP04

Feature: HANA NSE, HANA Extension Nodes, HANA Dynamic Tiering, SAP IQ

The HANA data architecture is based on a pure columnar database architecture that allows customers to simply implement data models as wide and as deep as they need them to be. Allowing many solutions to be derived from a single real-time but holistic view of the data while lowering the total cost of ownership of the solution.

◈ Agile (time to deliver)
   ◈ Technology supports the ability to quickly adapt to the needs of the business.
   ◈ Respond to business requests in a timely fashion.
   ◈ Days or hour not weeks or months.
◈ One copy of the truth (minimize data duplication)
   ◈ Store the seed level data and operate directly against it
   ◈ Copies of data introduce risk and are prone to error
   ◈ Aggregation of data reduces value as details are lost
◈ Run-Live (real-time)
   ◈ Data has a time-based value
   ◈ Data loses value as time passes
   ◈ Business gains agility by being able to respond to current data

HANA Data Consumption

Product: SAP HANA 2.0 SP04

Feature: SAP Analytics Cloud

We will examine how to deliver the enterprise analytic models to visualization tools while doing all of the heavy lifting analytical processing of the data at the SAP Intelligent Digital Business Platform level.