Going Cognitive with IBM

Atlantic GrupaMaja Vekic Vedrina

WatsonWatsonWatsonWatson SEE Summit 2017

Atlantic Grupa – Who we are?

Corporate needsOverview over whole company

HeterogeneousVarious businesses

Company cultureCreativity, innovation

Local needsSpecifics of the each of the businesses

GrowthFast changes

Our Environment

Operational AnalyticsOperational Analytics Advanced AnalyticsAdvanced AnalyticsPredictive and

Prescriptive Analytics

Predictive and Prescriptive

Analytics

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Building Analytical Capabilities in Atlantic Grupa

Single Version of the Truth

Data Reusability

Self-Service for internal users

Different:• users• needs• skills

Data:centralised

Analytics: decentralised, democratic

Governance Model

Analytical Centre of Excellence

Guidelines

Decisions, Principles and Choices

Architecture in Analytics Domain of Atlantic Grupa

EnterpriseData Warehouse

ETLIBM Data Stage

Data Sourc

es

LocalData

Warehouses

ETLIBM Data Stage

Local Layer Corporate Layer

Cognitive Analytics

Watson Analytics

Da

ta

Analytics

Master Data Services (Microsoft)

Reporting &

Visualisation

Cognos BI

Advanced Analytics

SPSS Modeller

Financial ConsolidationCognos Controller

PlanningCognos TM1

Using IBM Watson Analytics in Atlantic Grupa

Experience Sharing

Going cognitive with IBM Atlantic GrupaMaja Vekić Vedrina

Important findings that can make a difference

What the Tool Does?Many business questions

Agilegetting fast from business questions to insights

Watson Analytics

Business action

Human Resources

Sales

Marketing

Internal Audit

Logistics & Distribution

Watson Analytics Use Cases in Atlantic Grupa

Our Learning (1/4)

• Fits well with users who work in ad-hoc/discovery mode

• Saves the time significantly

• Brings advanced analytics closer to the „standard” user

• Helps in closing the gap of resources with rare skillsU

sers

Our Learning (2/4)

Da

ta

• Don’t underestimate data preparation process

• Data have to be in proper format and well structured

• Standard topics are still important:

• data integration

• data enrichment

• single version of the truth

• governance

• Dataset which enters into analysis is limited to 100.000 rows

• Analytical capabilities of Watson Analytics are not unlimited -> continue work in another tool (i.e. SPSS Modeller)But, helps tremendously in selecting predictors (saves time)

• Several products are part of Watson platform => it can be confusing for the customer

• Constant development => new features with new releases

Our Learning (3/4)

Ch

all

en

ge

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• Integration between Watson Analytics and Cognos BI

• Watson Analytics –> in cloud

• Cognos BI –> on premise

• Connectivity to on premise databases

• Re-using the integrated and well structured data from DWH and Cognos BI

Our Learning (4/4)

Arc

hit

ec

tur

e

Syn

erg

ies

Ineterested

users

Relevant use cases

Dedicate the time

Training available online

Experiment with the tool and data =>

learn

How to start with Watson Analytics (Our Way)

Questions & Answers

Atlantic GrupaMaja Vekic Vedrina