1

SAP HANA SQL Datawarehousing

Ausape. Zaragoza

YOUR EVERYTHING INNOVATION PARTNER

June 5th, 2019

Confidential and Property. © 2019 UST Global Inc.

2

Jorge Porca

▪ Especializado en “Data & Analytics”.

▪ Más de 15 años trabajando en distintas compañías desarrollando y

adaptando plataformas de Datawarehousing y BI a las necesidades

del negocio en sectores como retail, turismo, seguros, sanidad y

fabricación.

▪ Instructor oficial para SAP Education Spain desde hace más de 10

años.

▪ BW4, HANA, BPC, SAC, Predictive Analysis ML.

Speaker BIO

3

Agenda

SAP BW4HANA - Plattform for Data Warehousing

SAP HANA SQL Datawarehousing Toolset

▪ Model the SAP HANA SQLDW

▪ Develop the SAP HANA SQLDW

▪ Deploy the SAP HANA SQLDW

▪ Run the SAP HANA SQLDW

Summary

4

SAP BW4HANA - Plattform

for Data Warehousing

5

SAP BW4HANA

HANA 2.0

SAP BW/4HANA – The Next Generation Data Warehouse

SAP BW 7.5powered by SAP HANA

Performance

optimization

Simplification and Virtualization

Introducing SAP BW/4HANA

The Next Generation Data

Warehouse

Logical Data Warehousing

Internet of Things

Integrates with Big Data

Simplification,

HANA platform

integration

Big Data

scenarios

2013 20152012

SAP BW 7.3powered by SAP HANA

SAP BW 7.4powered by SAP HANA

2016+

SAP BW/4HANAStarterAdd-on

For SAP BW/4HANA

customers only

Use transfer tools

to make system ready

for SAP BW/4HANA

Requires SAP BW

7.5 SP 4 or higher

6

SAP HANA Platform

7

The Three Approach-Strategy for SAP HANA Data Warehousing

Application driven approach, SAP BW/4HANA as

premium DW application with integrated services

▪ SAP BW/4HANA is an application offering. All data

warehousing services via one integrated repository

▪ Optional integration of additional tools for modelling,

monitoring and managing the data warehouse

SQL driven approach, SAP HANA with loosely coupled

tools and platform services, logically combined

▪ SQL approaches require several loosely coupled tools, usually

having separate repositories

▪ “Best of breed” approach to build your own model

SAP HANAPlatform

SCHEDULING &

MONITORINGMODELING PLANNING

OLAPLIFECYCLE

MANAGEMENTETL

SAP BW/4HANA

SAP HANAPlatform

SCHEDULING &

MONITORINGMODELING PLANNING

OLAPLIFECYCLE

MANAGEMENTETL

HANA SQLDW

Application Services Integration Services Processing Services Database Services

Integration Services Processing Services Database ServicesApplication Services

8

The Three Approach-Strategy for SAP HANA Data Warehousing

SAP HANA Platform

SAP BW/4 approach SQL approach(extendable by third-party-tools)

Mixed approach

Data Warehouse

SAP HANA

Application

Services

SAP HANA

Integration

Services

SAP HANA

Processing

Services

SAP HANA

Database

Services

SAP Business Warehouse

SAP BW/4HANA

SAP HANA native

SQL Data Warehouse

9

Drivers for Change in the Data Warehouse environment

TIME TO VALUE

Reduced deployment times

& involvement of business

(Industry Data Models)

IT PROFESSIONALS

New hires look for innovative

technologies and exciting projects

COMPLEXITY

Data is distributed in

different systems

COMPETITION

Use data and new technology

to stay competitive

PERFORMANCE

Immediate response &

system stability expected

OPEN PLATFORM

Leverage existing skills

and open standards

10

SAP HANA SQL

Datawarehosing Toolset

11

Integrated Data Warehouse Process

SQL ToolSet

DESIGN RUNDEVELOP DEPLOY

12

Integrated Data Warehouse Process

Design Phase

SAP Enterprise Architect Designer

Model across the enterprise

Native HANA 2 application

DESIGN RUNDEVELOP DEPLOY

12

13

SAP Enterprise Architecture DesignerEdition for SAP HANA

Create and integrate enterprise, landscape,

process and data models to manage information

and systems effectively

▪ Business process architecture

▪ Landscape and application architecture

▪ Requirements management

▪ Strategy architecture to document goals

and projects

▪ Physical data modeling & data

architecture

▪ Reverse engineering capabilities

▪ Lineage & Impact analysis

Design

Implementation

Strategy

TechnologyBusiness

Process

Data

Landscape

Requirements

13

14

SAP Enterprise Architecture Designer

14

Specifics for SAP HANA

▪ Reverse-Engineering capabilities

▪ Impact Analysis, Model Comparison

▪ Generate EAD model objects in HANA HDI

compatible file format

oTable & View

oData Movement Model (Flowgraph)

oNative DataStore Object (NDSO)

oVirtual table definition

oHANA CDSAssociation

▪ Storage of generated HANA HDI compatible files to

o Local ZIP-File (SAP Web IDE - Import)

oGit Repository (SAP Web IDE - Git Integration)

15

Demo

15

Demo Enterprise Architecture Designer

16

Building the SQL DWOne environment to build all artefacts

SAP Web IDE for HANA

Develop the entire DW from your browser

Successor of HANA Studio Dev

Major extensions for DWF (Flowgraphs, NDSO, DLM, Taskchains)

DESIGN RUNDEVELOP DEPLOY

16

17

SAP Web IDE for SAP HANA

▪ SAP Web IDE for SAP HANA is the successor to

SAP HANA web development workbench and the

development perspectives of SAP HANA studio.

▪ It offers

o Development of SAP HANA content and

models

o UI development with SAPUI5

o Development of polyglot applications

o Node.js, Java or XSJS business code

o Git integration

▪ It is

o Browser based

o Installed as a SAP HANA XSAapplication

17

18

▪ NDSO provide a central persistency object with

additional semantics to determine delta and

▪ NDSO was established to model HANA

SQL Data Warehouse systems

▪ NDSO handle multiple Inbound-Queues (NDSO

o InboundQueue) to load data from different

sources

▪ NDSO allows merging of delta data and full data

loads into its reportable content and also provides

delta-data processing capabilities to connected

data targets

▪ NDSO data merge process triggered by the

NDSO- Activation Process/Step

▪ The NDSO is capable to process records based on

the Source-data specified RECORDMODE values

(like: INSERT

o / UPDATE / DELETE – aka. CDC-Pointer)

Native DataStore Object (NDSO)

18

19

Demo

19

Demo Web IDE for Hana

20

Deploying the SQL DWThis is where DevOps comes

in

DESIGN RUNDEVELOP DEPLOY

Open Source deployment

Bring your own tools: Jenkins,

Bamboo, XL release, etc.

20

CTS+

XSA integrates with

enhanced change and

transport system (CTS+)

21

Classic DWH developmentAll developers work in the same workspace and runtime, on the same

version

▪ In HANA XS Classic, or in a

common best-of-breed data

warehouse project, all

developers work on the same

repository and the same run-

time environment.

▪ Any change made by one

developer and activated on the

database, in the ETL tool, or

other tooling, is immediately

visible for all other developers.

▪ This “shared workspace” and

“shared runtime” make it hard to

develop and test features or user

stories isolated from other

developers.

25

22

Developer and feature

isolationEnabling parallel development and test

▪ In HANA XS Advanced, all

developers work in their isolated

workspace.

▪ Each developer also works with

an isolated runtime. HANA XS

Advanced automatically creates

a runtime container for each

developer.

▪ All developed objects are stored

in a shared repository: GIT,

which keeps a full version

history, and uses branching to

support isolated feature

development.

GIT

repository

(continuous)

Testing

Deployment

27

23

Versioning and development with GITWorking in parallel on different repository

versions

User story 1

User story 2

Master

Time

23

24

Demo

24

Demo Deploy - Github

25

Deploying the SQL DWThis is where DevOps comes in

DESIGN RUNDEVELOP DEPLOY

EIM & DWF Monitoring

EIM, Scheduler & NDSO Monitor

Build into Webide

25

Data Lifecycle Manager

Data Warehouse Foundation

PowerDesigner &

Enterprise Architect Designer

Data Lineage

2626

FlowGraphs

27

Data Lifecycle ManagerData Warehouse Foundation

SQL Data

Warehousing

In-Memory

(Hot Store)

Dynamic Tiering

(Warm Store)

TBs - 10s of TBs 10s of TBs - PBs

Data Lake

(Cold Store)

SAP Vora

HADOOP

SAP IQ

DLM Generated

Union & Pruning CalcViews

Structured data

for fastanalytics

Less frequently

accessed,

structureddata

Raw data:

semi-structured,

unstructured,

streaming data etc.

DLM

DLM managed data placement

Based on aging rules

27

28

Summary

29

Building Agile & Data Driven Applications SQL Datawarehousing

GitSAP DWF

SAP Web IDE

SAP AC

D

P

SAP EAD

SAP EAD

CI / CD

Git

CI / CD

Legend:

SAP EAD – SAP Enterprise Architecture Designer

SAP AC

SAP DWF

CI / CD

– SAP Analytics Cloud

– SAP Data Warehousing Foundation

– Continuous Integration / Continuous Deployment

30

Strengths

▪ Complete web approach with HANA XS Advanced platform. Still

100% open SQL approach.

▪ Strong and open repository versioning with Git

▪ Freedom to custom built data models and data management

processes. Example: adopt Data Vault model.

▪ Leverage 3rd party tools and in-house standards, skills &

knowledge

▪ DevOps enabler: Continuous Testing | Integration | Deployment

Use Case

▪ Considerable share of non-SAP source systems and interfacing

▪ Specific data model requirements, for example for for auditability

▪ 3rd party DW replacement

▪ DevOps requirements

Why should you choose HANA SQL DW

SAP HANA Platform

SCHEDULING &

MONITORINGMODELING PLANNING

OLAPLIFECYCLE

MANAGEMENTETL

HANA SQL DW

31

Model,

Compute

& Data Store

Ingest

Sources

Consume

Data Lake

ETL Replication Streaming Virtual Access …

3rd-PartyAnalytics

Sensor Machine

…

SAP Vora

BI | Predictive | Planning Machine Learning

SAP WebIDE

For SAP HANA

SAP Power

Designer /

SAP Enterprise

Architecture

Designer

Git-Hub

HANA SQL Data WarehouseData process perspective of SAP defined SQL DW

31

SAC

32

Preguntas??

33

Gracias!!