Úvod do s/4hana · a common database approach for oltp and olap using an in-memory column database...

8
20. listopadu 2018 Zdeněk Panec, SAP ČR, spol. s r. o. Úvod do S/4HANA

Upload: others

Post on 20-Aug-2020

3 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

20. listopadu 2018

Zdeněk Panec, SAP ČR, spol. s r. o.

Úvod do S/4HANA

Page 2: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

2INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ

Paradigm shift

Again

1970´ 1990´ 2010´

In-

Memory

➢ everything mobile

➢ everything cloud

➢ everything in memory

2013 Vision

Page 3: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

3INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ

R/2

1979

R/3

1992

ERP

2004 2015

What is SAP S/4 HANA

▪ On premise

▪ Cloud

▪ Hybrid

45 years of innovation across industries

300,000+ customers

74% of the world’s transaction revenue touches an SAP system

Always providing multiple ways of innovation adoption

• Integration

• Standardization

• Globalization

• Trust

Page 4: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

4INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ

Role-basedengagement across the company

Instant accessto any business insight

Simple designacross business processes

Personalized

Responsive

Simple

SAP Fiori Library

SAP S/4HANA - Simple role-driven user experience

Page 5: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

5INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ

A Common Database Approach for OLTP and OLAP Using

an In-Memory Column DatabaseHasso Plattner

SAP HANA

platform

OLTP* + OLAP**

SAP HANA

simplifies

1010100101010010010100110101101101110100100010011011001

OLTP*

ETL

OLAP**

Replication Replication

Transactions AnalyticsTransactions Analytics

1010100101010010010100110101101101110100100010011011001

Rethink data management for real-time business

Page 6: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

6INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ

Used for Master Data only

MATDOC_

EXTRACTMSEGMATDOC

On the fly aggregation and compatibility views for indices and obsolete tables

DocumentHeader incl.

StatusItem incl.

Status

VBFA

(simplified)

PRCD_

ELEMENTS (new)

FAAT_PLAN

_VALUES

ACDOCA

FAAT_YODA

FAAT_DOC_IT

Document

Header Item

MSPR

MARC

MKOL MSLB

MARD

MSKA

MSKUMCHB

MLDOCCCS

MLDOCMBEW

QBEW

OBEW

EBEW

BSEGBKPF

VBRPVBRP

VBAPVBAK

LIKP

VBRK

KIPS

VBAPVBAK

VBUP

LIKP

VBRK

LIPS

VBUK

Material Quantities

VRPMA

VBOX

VAKPA

VLKPA

VAPMA

LKPMA

KONV

VRKPA

VBFA

Item

Indices

FAGLF

LEXA*

BKPF

LFC3

COSSCOBK

FAGLF

LEXT*

KNC1

COEP

ANEK ANEA

GLT0 KNC3

ANEP

BSEG

MLHD*

LFC1

MLIT*

Sales

MLCR*

ANLC

COSP

ANLP

MLCD*

BSAD

FAGL

BSIS

BSIKBSIS BSAS

BSID

CKMI1*

BSAK

FAGL

BSAS

BSIM*

Totals Indices

Finance

MSTEMKPF

MSLB

MSSLMSSA MSSQ

MSTQ

MSKUH

MSTB

MARC MCHBH

MKOL

MCHB MSKUMARD

MSKA MSPR

MSTQH

MKOLHMARCH

MSSQHMSSAH MSTBH

MSTEH

MSPRH

MARDH

MSLBH

MSKAH

Material Document

Stock Aggregates

History

Sales Order

Delivery

Billing Document

Status Info

Conditions

Document Flow

GL, AR, AP

New GL

CO

AA

ML

Index for Rebates

SAP Business Suite

Header Item

Hybrid: Master Data with Stock Aggregates

Aggregates

MBEWHMBEW

OBEWH

EBEW

QBEW QBEWH

EBEWH

OBEW

CKMLCR

CKMLPP

Valuation in MM or Valuation in ML

Material Values

Aggregates

Inventory movements

HistoryUsed for Master Data onlyHybrid: Master Data with

Valuated StockML Valuation

MLHD

MLIT

MLPP

MLCR

MLCRF

MLKEPH

CKMLPP

CKMLCR

MLCD

CKMLMV003

CKMLPPWIP

CKMLKEPH

CKMLMV004

SAP S/4HANA Database & Table StructuresPrepare your data structures for new real-time requirements, big data, and high throughput

Page 7: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

7INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ

SAP S/4HANA

Database compression with TCO impact

Database Footprint

Reduction in

SAP Simple Finance

Suite on HANA S/4HANA

Actual

(S/4HANA with split into

Actual / Historical data)

Suite on

Traditional DB

593 GB

118.6 GB

42.4 GB

8.4 GB

Replace totals with on-the-fly aggregation.

Replace secondary indices with dynamic

projection and selection.

Data Aging

5 fiscal years in the

system, 1 year aging

frequency

Compression in

columnar storage

Do not forget dev + test system + back up & recovery

Page 8: Úvod do S/4HANA · A Common Database Approach for OLTP and OLAP Using an In-Memory Column Database Hasso Plattner SAP HANA platform OLTP* + OLAP** SAP HANA simplifies 10101001010

8INTERNAL© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ

SAP S/4HANA Adoption

Largest User base

SAP S/4HANA Finance 155.500

SAP S/4HANA full scope 100.000 (in Q4/2018)

HANA Memory

SAP S/4HANA Finance: The biggest live system is 16T and the

second largest is 12T

SAP S/4HANA: The biggest live system is 12T, 40T in

implementation, 30T in implementation (with 60T planned in

2020)

Project Type

Installed base projects

1/3 New installations vs. 2/3 System Conversion

Average duration approx. 7-8 months

Total Count

Projects: -> 3.000 of which 80 % are full scope

Productive: > 1.400 of which 65 % are full scope