sap forum ankara 2017 - mds ap verİnİn merkezİne seyahat

SAP FORUM ANKARADijital Dönüşüm

Verinin Merkezine Seyahat

Konuşmacı Adı : İlker Taşdemir

Firma Adı : İş Analik Çözümleri Grup Direktörü – MDS ap

© 2017 SAP AG or an SAP affiliate company. All rights reserved. 2

Eastern Europe

Middle East

Africa

49+ years of Experience in IT (Since 1967)

4500+ Employees in 30 countries across 3 continents

150+ companies unified under the group

100+ top resellers awards from global IT Leaders

A 4 billion USD Leader offering stability & high Integrity in Technology & Solutions

SAP Partner Centre of Excellence

MDS AP Tech Overview

a MIDIS Group Company

Over 24 Years of in depth experiences helping customers Manage, Integrate,

Analyze and Mobilize Business Mission critical Data across the enterprise;

Exceptional track record providing Turnkey IT Solutions across Turkey, Middle

East & Europe.

A Unique Partnership with SAP; Implementing Excellence; Optimizing

Application Management

Strategic long term partnerships with our customers; Focusing on Customer

Satisfaction and Technology Innovation

Help customers better use their data assets to improve business performance

and make smarter decisions


Data Management Enterprise

Performance

Management

Business Analytics Enterprise

Architecture

Omnichannel and

Cloud Solutions

• OLTP & Real Time

Database

• High Performance

Analytic database

• Data Archiving

• Data Replication

• Data Connectivity

• Security & Auditing

• Disaster Recovery

• Big Data

• Strategy Management

• Budgeting and Planning

• Financial Consolidation

• Profitability and Cost

Management

• Disclosure management

• IFRS9 Reporting

• Operational & Analytical

Reporting

• Executive Dashboards

• Predictive Analysis

• Data Discovery &

Visualization

• Enterprise Data

Warehousing

• Data Modelling

• Complex Event

Processing

• Data Quality Management

• Master Data Management

• Meta Data Management

• Enterprise Integration

• Analytical LOB Apps

• Data Modelling

• Business Process

Modelling

• Zachman framework

• TOGAF methodology

• e-Commerce

• e-Marketing

• CRM

• HRMS

• e-Banking

• Mobile Banking

• Omnichannel Solutions

MDS AP TechPractices Overview


MDS AP with the best of breed SAP Business Analytics Platform

provides complete Agile Visualization & Advanced Analytics

Solutions that optimize Any Data Variety, regardless of its

structure, at Real-Time Velocity, to deliver next generation analytics

Our Mission is to provide high quality service to our strategic

customers by delivering world class solution offerings with high

integrity, commitment and professionalism.

Our Vision is to become the leading partner that brings value

to our customer base.

Our Differentiators


Rich EcosystemOver 25 Partners

http://www.bradmark.com/index.html

http://www.bradmark.com/index.html


Customer BaseOver 400 Enterprise Customers

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http://www.yapikredi.com.tr/Default.aspx

http://www.yapikredi.com.tr/Default.aspx

Verinin Merkezine

SeyahatDATA


Verinin Tarihçesi

40,000 BCE

Cave drawings and tally(bone) sticks. These are used to track trading activity and record inventory2400 BCE

The abacus is developed, and the first libraries are built in Babylonia

300 BCE – 48 AD

The Library of Alexandria is the world’s largest data storage center

100 AD – 200 AD

The Antikythera Mechanism – the first mechanical computer – is developed in Greece

1928

Fritz Pfleumer creates a method of storing data magnetically, which forms basis of modern digital data storage technology.

1970

Relational Database model developed by IBM mathematician Edgar F Codd. The Hierarchal file system allows records to be accessed using a simple index system. This means

anyone can use databases, not just computer scientists.

1991

The birth of the internet. Anyone can now go online and upload their own data, or analyze data uploaded by other people.

2005

Hadoop – an open source Big Data framework now developed by Apache – is developed. The birth of “Web 2.0 – the user-generated web”.

2008

Globally 9.57 zettabytes (9.57 trillion gigabytes) of information is processed by the world’s CPUs.

An estimated 14.7 exabytes of new information is produced this year.

2010

Eric Schmidt, executive chairman of Google, tells a conference that as much data is now being created every two days, as was created from the beginning of human

civilization to the year 2003.

2016

1.3B people on business and social networks today. 1 Yottabyte has been reached and it’s predicted

that by 2020 we’ll reach 6 Yottabytes (6,000 exabytes).


Verinin DeğişimiData Type Range Max Precision

CHAR(n)

CHARACTER(n)

1<=n<=32K-1

1<=n<=32K-1

n/a

n/a

VARCHAR(n)

CHARACTER

VARYING(n)

1<=n<=32K-1

1<=n<=32K-1

n/a

n/a

INTEGER/INT

UNSIGNED INT

-2(^31)<=n<=2(^31)-1

Or –2,147,483,648 and 2147483647

0 TO 4294967294

10

TINYINT 0<=n<=255 3

SMALLINT -2(^15)<=n<=2(^15)-1

Or

-32,768 to 32,767

5

BIGINT(n)

UNSIGNED

BIGINT(n)

-9.2(^18)<=N<=9.2(^18)-1

Or

0 and 1.8(^19)-1

20

FLOAT(precision) Platform-dependant 16

REAL(precision) Platform-dependant 7

DATE Jan 1, 0001 to Dec 31, 9999 n/a

DATETIME

SMALLDATETIME

TIMESTAMP

0001-01-01 00:00:00.000000 to

9999-12-31 23:59:59.999999

n/a

TIME 00:00:00.000000 to

23:59:59.999999

n/a

DECIMAL(p,s)

NUMERIC(p,s)

-1038 to 1038-1 126

DOUBLE 2.22(^-308) to 1.79(^308) 15

BIT 0, 1 n/a

MONEY 19

SMALLMONEY 10

BINARY (length) n/a

UNIQUEIDENTIFIERSTR 36 n/a

VARBINARY (length) n/a

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=15132997&query_hl=8&itool=pubmed_docsum


http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=8259518&dopt=Abstract
















http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=retrieve&db=pubmed&list_uids=11533658&dopt=Abstract




http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Retrieve&list_uids=10205174&dopt=Abstract






































http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&dopt=Abstract&db=PubMed&list_uids=15454084











Semi/Unstructured Data Grows 7x Faster Than Structured!


What is Semi/Unstructured Data?

Are these data sets?

“Unstructured” data


Semi/Unstructured sources

Consider:

Web pages, E-mail, news & blog articles, forum postings, and other social media.

Contact-centre notes and transcripts.

Surveys, feedback forms, warranty claims.

And every kind of corporate documents imaginable.

Date: Sun, 13 Mar 2005 19:58:39 -0500

From: Adam L. Buchsbaum <[email protected]>

To: Seth Grimes <[email protected]>

Subject: Re: Papers on analysis on streaming data

seth, you should contact divesh srivastava,

[email protected]

regarding at&t labs data streaming technology.

adam

SURVEY

EMAIL


Semi/Unstructured Data

Date Time Location Type Officer Report02/02/2007 15:30 Phoenix Robbery John Smith Officer Smith arrested Pat Fitzgerald near Safeway on Tuesday. He was driving a green

Acura TL. Pat Fitzgerald stole Nintendo wiis on 01/02/2007 from Walmart. He was

transporting the Nintendo wiis to Mike Lewis in Phoenix.


Understanding the data is key to success

Sense & Respond Predict & Act

Raw

Data

Cleaned

Data

Standard

Reports

Ad Hoc

Reports &

OLAP

Generic

Predictive

Analytics

Predictive

Modeling

Optimization

What happened?

Why did it happen?

What will happen?

What is the best that

could happen?

Com

petitive A

dvanta

ge

Analytics Maturity


Your mobile device knows more and more about you each day

Where you are

Where you’ve been

Where you are likely to be going to

Who you’ve met

Who you are going to meet

Who you call

Who calls you

Who you TXT-IM-link

All your contacts and their details

All your URLs

All your passwords

What you are doing now

What you’ve done in the past

What music you listen to

What movie you watch

What news/books you read

What apps you use

How much you’ve slept

How much you’ve exercised


Complex Data and Lightning Action

Traditional BI: “How many negative comments/fraudulent

transactions occurred last week in Istanbul?”

Complex Event Processing: “When 3 negative comments or

suspicious transactions occur in any 5 seconds in Istanbul,

check the comment/transaction and execute the workflow”


The New ROI: Return on Data

Source: IDC Study: Realizing the Data Dividend, 2014.

The formula

[data + analytics + people ]

@

speed

Key Opportunity

AreasOrganizations can realize

Return on Data in several

key areas…

Productivity

Includes strategic

planning, human

capital management,

IT optimization

Operations

Includes demand

and supply chain

management,

logistics

Return

on Data

$674

billion

Return

on Data

$486

billion

Return

on Data

$158

billion

$235

billion

$1.6 trillionReturn on Data

18

Return

on Data

Customer

Facing

Includes customer

acquisition, retention,

support and pricing

Innovations

Includes service,

research and

development

innovation

Veri Teknolojileri


Imagine If You Could…

Reduce recall times

from 8 months to 8

minutes

Identify new fraud

patterns in seconds

vs. days

Access and

manage petabytes

of data

Avoid criminal

liability for

improper data use

in regulated

industry scenarios

And save up to

$20M in risk

exposure

And cut potential

fraud costs by

$71M

And reduce

costs by $2M

Ensure data

lineage, access

rights, and security

in Hadoop


What’s Stopping Us?The Digital Divide between Enterprise and Big Data

© 2016 SAP SE or an SAP affiliate company. All rights reserved. 21

Too Complex Too Slow Unable to

Work Together

ENTERPRISE BIG DATA


ENTERPRISE BIG DATA

Bridging the Digital Divide

Introducing

SAP HANA Vora

© 2016 SAP SE or an SAP affiliate company. All rights reserved. 22


Why SAP HANA Vora? Bridging the Digital Divide for Analysts, Developers, DBAs, and Data Scientists

Simplify Big Data

Ownership

Democratize Data AccessFor data science discovery

Precision Decision MakingIn enterprise apps + analytics

Business coherence

On-demand correlation

New insights from

aggregated data

Interactive data

Enrich the candidate

data sets

Simplified landscape

Improved correlation with

historical data


SAP HANA VoraWhat’s Inside and What Does It Do?

Democratize

Data

Access

Make

Precision

Decisions

Simplify

Big Data

Ownership

SAP HANA Vora is an in-memory query engine which leverages

and extends the Apache Spark execution framework to provide

enriched interactive analytics on Hadoop. Drill Downs on HDFS

Mashup API Enhancements

Compiled Queries

HANA-Spark Controller

Unified Landscape

Open Programming

Any Hadoop Clusters


YARN

HDFS

Enable Precision DecisionsWith Contextual Insights In Enterprise Systems

Other Apps

Files Files Files

HANA-Spark Controller for improved

performance between distributed systems

Gain business coherence with business data and big data

Compiled queries enable applications &

data analysis to work more efficiently

across nodes

Familiar OLAP experience on Hadoop

to derive business insights from big data

such as drill-down into HDFS data

Compiled

Queries

Spark

Controller

Drill Downs

SAP HANA in-memory platform

Vora

Spark

Vora

SparkIn-Memory

Store

Application Services

Database Services

Integration Services

Processing Services

SAP HANA Platform

Vora

Spark

HANA Smart Data

Access Spark

Controller


Democratize Data Access for Data Science Discovery

Extensive programming support for

Scala, python, C, C++, R, and Java allow

data scientists to use their tool of choice,

Pursue new inquiries without compromise on data and

easily integrate these insights with all data

Enable data scientists and developers

who prefer Spark R, Spark ML to mash

up corporate data with Hadoop/Spark

data easily

Optionally, leverage HANA’s multiple

data processing engines for developing

new insights from business and

contextual data.

Mashup

Enhancements

Open

Programming

Optional Use of SAP HANA for

Delegated, multi-engine pre-processing

Spark Data-source

API enhancement

In-Memory

Store

SAP HANA Platform

YARN

HDFSFiles Files Files

Vora

Spark

Vora

Spark

Vora

Spark

Application Services

Database Services

Integration Services

Processing Services


Imagine How SAP HANA Vora Can Change Your Business…

Adjust your sales force

and business

resources on the fly

based on real-time info

Understand what

customers are saying

about your marketing

messages

Find fresh opportunities

for product distribution

from detailed and

archived data

And simplify your

big data

management

And work in real

time with access to

all the data

And react quickly

with fresh insights

from the data lake

And beat your

competition to new

markets with

precision targeting

Manage data as a

single system, not a

collection of fragments


SAP HANA Vora: Financial Services Use Case

Fraud

Detection

Get access to all your data

including historical and

contextual trends and

current business data

to analyze anomalies

Risk

Mitigation

Be assured of more

precise data to perform

Monte Carlo simulations to

produce distributions of

possible outcome values

with more precise context

Targeted Marketing

Campaigns

React rapidly to customer

sentiment and pinpoint

targeting for sales and

marketing campaigns with a

more complete view of

customer needs and wants

360° Customer

Service

Ensure a more complete

picture of the customer with

analysis of unstructured

customer data, such as social

media profiles, emails, calls,

complaint logs, discussion

forums, and website history


SAP HANA Vora: Utilities Use Case

Predictive

Maintenance

Access complete historical

information and optimize

maintenance of critical

components and low tension

devices

Grid Planning

Generate more precise

simulations with access to

more data and forecast

consumption and production

based on weather, load

profiles, and other criteria

Smart Meters

Capture and analyze real-

time data from smart meters

to quickly respond to

emergency situations with

drill-down analysis.

Pipeline Monitoring

Protect pipelines through

continuous monitoring

across the regions.

Perform root-cause

analysis in case failure.


SAP HANA Vora: Telecommunications Use Case

Network Capacity

Planning

Access unified data from

multiple sources for a

unified OLAP view and

analyze call detail records

(CDRs) and network load

and plan infrastructure

expansions with greater

precision

Real-time Bandwidth

Allocation

Unify big data with business

data in-memory for real-time

response, and steer traffic

and optimize network quality

of service (QoS) to ensure

high service levels

Cellphone Service

Improvement

Combine ERP, CRM,

billing, and quality data in

one place for real-time

analysis to better manage

equipment placements,

leases, and services,

reduce costs, and increase

customer satisfaction

Targeted Network

Maintenance/Upgrades

Analyze machine data for

precise decisions about system

placement and reveal

opportunities for greater

incremental revenue


SAP HANA Vora: Healthcare Use Case

360 Patient

View

Gain a more complete

picture of the patient by

bringing together test,

genomic, archive, patient

care, and patient history

data into one unified view

Insurance/Medicare

Fraud Analysis

Search claims data from

many raw sources and

uncover previously hidden

fraud patterns

Managing Recalls &

Adverse Events

Quickly track affected

persons, reduce exposure,

and limit risk by leveraging

combined contextual and

business data to proactively

deliver information in

minutes, not weeks

Diagnosis and

Research

Synthesize data from many

raw sources, in real time,

such as combining patient

data with up-to-date

journal/medical data, and

speed diagnoses and

research efforts


Why SAP?

Technology designed from the

ground up to work with

distributed data at scale

The leading worldwide provider of

business applications with more than 40

years experience in delivering enterprise-

class applications

Leading-edge platform,

applications and business

network on premise and in the

cloud

SAP Enables

The Digital Enterprise

SAP Knows

Big Data

SAP Delivers

Worldwide Support


Try It Today

Access the Cloud Trial >

bit.ly/1K1qLyo

Read More About it >

http://go.sap.com/product/data-

mgmt/hana-vora-hadoop.html

Talk to Your SAP/MDSAP Rep >

bit.ly/1K1qLyo

http://go.sap.com/product/data-mgmt/hana-vora-hadoop.html

© 2017 SAP AG or an SAP affiliate company. All rights reserved.

Teşekkürler

İletişim Bilgileri:

İlker Taşdemir

İş Analik Çözümleri Grup Direktörü – MDS ap

+90 532 5499392

+971 50 7129169

[email protected]