The Essential of Data Insights for Executives¸›าฐกถา 3 The Essential of... · The...

Danairat T.

The Essential of Data Insights for ExecutivesThe Strategic Management Framework

1

Agenda

• Today Organization Alignment• What is Business Intelligence (BI)?• What is Business Analytics (BA)?• Example Cases• Big Data Project Management• Big Data Maturity Model• Big Data Governance• Summary

2

Introduction to Big Data 3Vs

Volume

Variety Velocity

DB TableDelimited Text

XML, HTML

Free Form TextImage, Music, VDO, Binary

BatchNear real time

Real time

GBTBPB

XB

ZB

3

Introduction to Big Data 5Vs

luizricardo.org4

Startups and Big Data

5

ApplicationAreas

SmartCities

SmartEnvironme

ntSmartEnergy

SmartAgriculture E-Health Retail Logistics Industrial

Control

Internet of Things

Monika, 2015

6

Retails Store Use Cases

1. Golden zones2. More expensive items

with bigger margins3. Endcaps4. Buy level5. Traffic builder6. Action alley7. Front of shop8. Signpost brands9. Hanging signs and

shelf signs10. Range reduction

Less can be more. Averagehousehold uses 300 products in ayear

independent.co.uk7

Retails Store Use Cases

Store Layout ProfitsCustomer Density

independent.co.uk8

การเตอืนภยัพบิตั ิ

Sensor ปรมิาณนําฝน นําในเขอืน ปรมิาตรเขอืน, แสดงแนวโนม้สภาวะนําท่วม Nearly Real-Time

9

1. B

lood

Pre

ssur

eH

eart

rate

Tra

ckin

g

4. H

ealth

Tra

ckin

gH

ealth

che

ck u

p re

cord

s

1. B

lood

Pre

ssur

eSl

eep

Trac

king

4. H

ealth

Tra

ckin

gH

ealth

che

ck u

p re

cord

s

3. Public/PrivateHospital executesHealth Program

integratedEHR/EMR Systems

2. Governmentcreates/revisesNational Health

Program

1. B

lood

Pre

ssur

eC

oach

Tra

ckin

g

4. H

ealth

Tra

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gH

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che

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cord

s

Big Data

Cloud

SuggestedHealth Improvement

(Secured Personal Access)

Government Officer

Doctor

Nurse

Officer

IntegratedMedical Device





Healthcare Big Data

10

Opportunity and Market Outlook

Source: Machina Research 11

จะทําโครงการ Big Data อยา่งไร และจะเรมิตน้Big Data ทจีดุไหนดี

Digital PlatformBig Data Digital

Security

“Innovation”“Efficiency”

“Sustainability”

Cloud

Vision,Mission

Statements

12



Security



Cloud

Vision,Mission

Statements

Danairat T.

จะเรมิตน้BigData อยา่งไร

13



Security



Cloud

Vision,Mission

Statements

กระบวนการทํางาน

กฎระเบยีบ

ขอ้มลูภายใน

งานดว่น ขอ้มลูภายนอก

โครงสรา้งและ

ภาระกจิ

14

Choose the Right Data Visualization

http://img.labnol.org/di/data-chart-type.png

15

What is Business Intelligence (BI)?

Business intelligence systems are used to maintain, optimize andstreamline current operations. BI improves and maintains operationalefficiency and helps businesses increase organizational productivity.Business intelligence software confers many benefits, notably powerfulreporting and data analysis capabilities. Using BI’s rich visualizationmechanisms, managers are able to generate intuitive, readable reportsthat contain relevant, actionable data.

Popular business intelligence solutions include; SAP BusinessObjects, QlikView, IBM Cognos, Microstrategy, etc.

https://selecthub.com/business-intelligence/business-intelligence-vs-business-analytics/16

What is Business Analytics (BA)?

Like business intelligence, BA collects and analyzes data, employspredictive analytics and generates richly visualized reports, helpingidentify and address an organization’s weak points. That’s where similaritiesend. Business analytics software is used to explore and analyze historicaland current data. It utilizes statistical analysis, data mining andquantitative analysis to identify past business trends.

Popular business analytics solutions include; SAP Business Analytics Suite, Pentaho BA, Birst BI and Tableau BIg Data Analytics.

https://selecthub.com/business-intelligence/business-intelligence-vs-business-analytics/17

BI / Descriptive / Diagnostic analytics

Descriptive/Diagnostic analytics answers the question, "Whathappened in the business?" It looks at data and information todescribe the current business situation in a way that trends,patterns and exceptions become apparent. This takes the formof reports, dashboards, MIS, etc.

mu-sigma.com18

BA / Predictive analytics

Predictive analytics answers the question, "What is likely tohappen in the future?" Here data modeling and forecasting areused to determine future possibilities

mu-sigma.com19

BA / Prescriptive analytics

Prescriptive analytics is the combination of the above to provideanswers to the "So what?" and the "Now what?" For example,what should a business do to retain key customers? How canbusinesses improve their supply chain to enhance service levelswhile reducing costs?

mu-sigma.com

Action!

20



Security



Cloud

Vision,Mission

Statements

Danairat T.

ใชเ้ทคโนโลยีใหส้อดคลอ้งกับเป้าหมาย

องคก์ร

21

ลําดบัขนัและความสอดคลอ้งดา้นเทคโนโลยี

โครงการด้านดจิิทัล

โครงสร้างพืนฐานด้านดิจิทลั

ภาระกิจNew

ServicesOptimizedServices

RetiredServices

Big Data DigitalSecurity



Cloud

Data Monetization

New Services, Channels

IoT, Smart Devices

Business ProcessOptimization/Outsourcing

Smart Workforce

EnterpriseMetamorphosis

โครงสร้างการทํางาน

กระบวนการทํางานและระเบียบการทํางานMore ControlMore Flexible

Vision,Mission

Statements

22

ความตอ้งการ Business Analytics และ Business Intelligence



RetiredServices




Cloud

Data Monetization


IoT, Smart Devices


Smart Workforce




Vision,Mission

StatementsBusinessAnalytics

BusinessIntelligence

• What will happen?• What if and Why did it happen?• Predictive Modeling• Simulation/Optimization• Advanced Statistic Models• Data Mining (Text, Multimedia)• Data Science

• Who did that task?• What happened?• Dashboards, Alerts• Scorecards

Monitoring• Slice & Dice,

Drilling• Reports

• Data Lake• DWH



23

Choosing between Business Intelligence (BI) andBusiness Analytics (BA)

While superficially similar, the difference between business intelligence vsbusiness analytics is clear:- BI uses past and current data to optimize the present for current

success.- BA uses the past and analyzes the present to prepare businesses for the

future.

Choosing the solution for your business depends on your aims.- If you are satisfied with your business model as a whole and mainly wish to

improve operations, increase efficiency and meet organizational goals,business intelligence may be an optimal solution.

- If you intend to change your business model and need to know where tostart, business analytics might be the best option.

https://selecthub.com/business-intelligence/business-intelligence-vs-business-analytics/

24

Choosing between Business Intelligence (BI) andBusiness Analytics (BA)

Business Intelligence (BI)BI has the added advantages of targeting a business’s weak areas and providingactionable solutions to those problems. Business Intelligence software is an excellentsolution for managers who want to improve decision making and understand theirorganization’s productivity, work processes and employees. And, with thatunderstanding, improve their business from the ground up.

Business Analytics (BA)If your organization is a new entity, or in the midst of significant changes, businessanalytics software is a serious contender. BA uses historical data, current information,and projected trends to ensure your business makes the right changes. Businessanalytics is the solution if you want to analyze your company, your market, and yourindustry with the dual goals of optimizing current performance and predictingbusiness trends to help you remain competitive in the future.

Most businesses want a combination of current success and future preparation. Alone or together, business analytics and businessintelligence can help you take your business where you want it to go.

https://selecthub.com/business-intelligence/business-intelligence-vs-business-analytics/ 25

Driving Data to Business Values

Data Inputs:-• Business Activities• Conversations• Web Logs• Social Media• Words• Picture• Voice• Videos• Sensors• Etc.

Business Values:-• Pricing analytics• Text Analytics• Sentiment Analysis• Relationship Analysis• Contextual Analysis• Face Analysis• Voice Recognition• Behavioral Analysis• Fraud analytics• Etc.

26

Big Data AnalyticsTechnology Platforms

27

Big Data Architecture

Big Data InfrastructureBig Data Infrastructure

Next Best Action BI/Report

Parallel Data Processing, Refinery

Ingestion and Acquisition

Distributed Data Store, Data Lake

Monitoring, ResourceManagement and

Metadata Framework

Security and ControlFramework

Predictive AnalyticsDescriptive/Diagnose Analytics Prescriptive Analytics

Big Data Platform

Big Data Applications

Compute Storage, Network

Fraud Analysis Cyber Security Talent Search

Staffs Managers PartnersCitizen ExecutivesExperts

28

Big Data System Implementation Architecture

Staffs Partners ManagersCustomers Executives Experts

Compute, Storage and Network Infrastructure

NoSQL with Maps DBCassandra, MongoDB, Neo4j

Data Analytics FrameworkR, Statwing, Pentaho, RapidMiner, Openrefine, DataCleaner, HIPI, Drill

HadoopHDFS, YARN, Spark, Storn, MRv2, Hive,

Mahout, Zookeeper, Mesos, Etc.

App1 ExecutiveReportsApp2 Advanced

Analytics

Syst

em M

onito

ring

Syst

em S

ecur

ity

Physical Building and Facility

Access Channels

Infra Platform Apps Access29

Big Data Project Life Cycle

Big DataPlanning

1. Identify Targeted Users2. Identify Target Opportunities / Key

Measurements3. Identify Data Sources/Types4. Identify Data Capturing Approaches5. Identify Data Processing and Visualization

Planning6. Identify Big Data Platform7. Identify Security8. Identify Governance and Change Control

for Operation9. Identify Team Structure10. Identify Phasing, Budget and Cost

Big DataDevelopment

1. Develop Use Cases2. Develop Requirements Definition3. Develop Big Data Solution

Framework4. Develop the Development and Test

Environment5. Develop Data Capture6. Develop Analytics7. Integrate Visualization8. Manage Assets and Configurations

Operation andSupport

1. Monitor Big Data PlatformAvailability, Utilization andCapacity Planning

2. Manage Operation Tasks (Admin.Scripts, Commands), DataCapturing System, Upgrading orPatching

3. Manage Service Requests andIncidents

4. System admin. Training5. Helpdesk Training6. End-User Training (Analytic

Results)

Evaluation

1. Adoption Rates for each analyticsresults

2. No. of Missing Analytic Results3. No. of Missing Data4. Lost hours per month5. Avg. of each Analytic Result

Response Time6. No. of Technology System Failure per

month7. Evaluate Activity Conformance with

Policies

30

Big Data People and Team Structure

Big Data ProgramCommittee

ProjectManager

Big DataArchitect Data Scientist Business

AnalystData

IntegrationSpecialist

Developer

Big DataEvangelist

31

Big Data Team Structure

No. Roles Description1 Big Data Program

CommitteeThe Team to develop Big Data initiative and deliver solution results

2 Big Data Evangelist The business evangelist must have a combination of goodcommunication and presentation skills and deep contextual businessknowledge, as well as a clear understanding of technology ingeneral and big data techniques.

3 Project Manager The project manager “owns” the development schedule and isexpected to ensure that the right architects, designers, anddevelopers are brought into the project at the right times.

4 Big Data Architect The person who has background in parallel and distributedcomputing architecture. This person is knowledgeable aboutfundamental performance “gotchas” that will impede the speed,scalability, and extensibility of any application requiring massive datavolumes.

32

Big Data Team Structure

No. Roles Description5 Data Scientist The data scientist combines knowledge of computer science, the

use of high-performance applications, and statistics, economics,mathematics, and probabilistic analysis skills.

6 Business Analyst The person who engages with the business process owners andsolicits their needs and expectations. Business analystswho are able to effectively translate business expectations intospecific data analysis results.

7 Data Integration Specialist The person who has experience in data extraction, transformation,loading, and data transformations in preparation for cleansing anddelivery to target systems. Seek people with experience with datafederation and virtualization, data quality, and metadata analysis.

8 Application Developer The technical resources with the right set of skills for programmingand testing parallel and distributed applications.

33

Big Data Project Life Cycle

Big DataPlanning

1. Identify Targeted Users2. Identify Target Opportunities / Key

Measurements3. Identify Data Sources/Types4. Identify Data Capturing Approaches5. Identify Data Processing and

Visualization Planning6. Identify Big Data Platform7. Identify Security8. Identify Governance and Change

Control for Operation9. Identify Team Structure10. Identify Phasing, Budget and Cost

Big DataDevelopment

1. Develop Use Cases2. Develop Requirements Definition3. Develop Big Data Solution

Framework4. Develop the Development and

Test Environment5. Develop Data Capture6. Develop Analytics7. Integrate Visualization8. Manage Assets and

Configurations

Operation andSupport

1. Monitor Big Data PlatformAvailability, Utilization andCapacity Planning

2. Manage Operation Tasks(Admin. Scripts, Commands),Data Capturing System,Upgrading or Patching

3. Manage Service Requests andIncidents

4. System admin. Training5. Helpdesk Training6. End-User Training (Analytic

Results)

Evaluation

1. Adoption Rates for each analyticsresults

2. No. of Missing Analytic Results3. No. of Missing Data4. Lost hours per month5. Avg. of each Analytic Result

Response Time6. No. of Technology System Failure

per month7. Evaluate Activity Conformance with

Policies

34

No. Phases Activities People Deliverables1 Planning Identify Targeted Users Big Data Program Committee Big Data Discovery Worksheet

2 Planning Identify Target Opportunities Big Data Program Committee Big Data Discovery Worksheet

3 Planning Identify Team Structure Big Data Program Committee Team Organization Chart

4 Planning Identify Data Sources/Types Big Data Architect, Data Scientist,Data Integration Specialist

Data Sources Types Information

5 Planning Identify Data CapturingApproaches

Data Integration Specialist, Data Scientist Data Capturing Information

6 Planning Identify Data Processing andVisualization Planning

Business Analyst, Big Data Architect, DataScientist, Developer

Data Processing Framework andUser Interface Summary

7 Planning Identify Big Data Platform Big Data Architect, Project Manager Big Data Platform Summary

8 Planning Identify Security Corporate Information Security, Big Data Architect,Project Manager

Security Scope Summary

9 Planning Identify Governance and ChangeControl for Operation

Internal Control Team, Corporate InformationSecurity, Big Data Architect, Project Manager

Governance, RACI, ChangeProcedures Summary

10 Planning Identify Phasing Budget and Cost CIO, CFO, Project Manager, Business Analyst Project Investment Summary

Key Activities, People and Deliverables

35

No. Phases Activities People Deliverables

1 Development Develop Use Cases Business Users, Business Analyst, Big DataArchitect, Big Data Evangelist

Use Cases Summary

2 Development Develop Requirements Definition Business Users, Business Analyst, Big DataArchitect

Requirements Summary

3 Development Develop Big Data Solution Framework Big Data Architect Solution Component Diagram

4 Development Develop the Development and TestEnvironment

Big Data Architect,Data Integration Specialist, Developer

Development and TestEnvironment

5 Development Develop Data Capture Data Integration Specialist, Developer Data Capturing Module

6 Development Develop Analytics Data Integration Specialist, Developer Data Analytic Module

7 Development Integrate Visualization Data Integration Specialist, Developer User Interface and VisualizationResults

8 Development Manage Assets and Configurations Project Manager, Big Data Architect, CorporateInformation Security, Head of IT Operation

Assets Inventory andConfigurations Change Procedure

Agile Methodology may apply in Big Data Development Phase.


36


No. Phases Activities People Deliverables

1 Operation andSupport

Monitor Big Data Platform Availability, Utilizationand Capacity Planning

IT Operation Team Availability, Utilization andCapacity Planning Report


Manage Operation Tasks (Admin. Scripts,Commands), Data Capturing System, Upgradingor Patching

IT Operation Team, Big DataArchitect

Schedule or Ad-Hoc OperationActivities


Manage Service Requests and Incidents IT Operation Team Service Requests and IncidentsProcedures


System Administration Training Big Data Architect,Data Integration Specialist,Developer, IT Administration, ITOperation

System Administration andOperation Training Activity


Helpdesk Training IT Administration, IT Operation, ITHelpdesk

Helpdesk Training Activity


End-User Training (Analytic Results) Business Analyst, Business Users End-User Training Activity

37


No. Phases Activities People Deliverables1 Evaluation Create Adoption Rates for each analytics

ResultsIT Operation Percent of user adoption

2 Evaluation Create No. of Missing Analytic Results Big Data Program Committee No. of Missing Analytics Report

3 Evaluation Create No. of Missing Data Results Big Data Program Committee No. of Missing Data Report

4 Evaluation Create Lost hours per month Results Big Data Architect, Data Scientist,Data Integration Specialist

Lost hours per month Report

5 Evaluation Create Avg. of each Analytic Processingand Response Time Results

Data Integration Specialist, Data Scientist Analytic Processing and ResponseTime Report

6 Evaluation Create No. of Technology System Failureper month Results

Business Analyst, Big Data Architect, Data Scientist,Developer

Technology System Failure permonth Report

7 Evaluation Evaluate Activity Conformance withPolicies

Big Data Architect, Project Manager Change Control Log Report

38

Big Data Project Worksheet

# Customerผู้ใช้รายงาน

Report Nameชือรายงาน

When to useใช้เมือไหร่

DataProcessing Typeวิธีการประมวลผล

DataProcessFramework

DataCapturing Method

DataNameDataSize/year

DataOwnerเจ้าของข้อมูล

1 Prime minister Flooding Status On demand (1-3 hrs) Descriptive Map Reduce WebService(JSON overREST)

400TB RID, GISTDA,Disaster

2 Prime minister Water way report Weekly Predictive Machine Learning Apache Strom 600TB GISTDA,GINFO

3 Prime minister Water management Monthly Prescriptive Deep Learning FTP 450TB สสนก, RID,WaterResource

Data Visualization Data Science Data Engineer

1. Plan

2. Execute39

Big Data Project Worksheet

# Customerผู้ใช้รายงาน

Report Nameชือรายงาน

When to useใช้เมือไหร่

DataProcessing Typeวิธีการประมวลผล

DataProcessFramework

DataCapturing Method

DataNameDataSize/year

DataOwnerเจ้าของข้อมูล

1 Prime minister Flooding Status On demand (1-3 hrs) Descriptive Map Reduce WebService(JSON overREST)

400TB RID, GISTDA,Disaster

2 Prime minister Water way report Weekly Predictive Machine Learning Apache Strom 600TB GISTDA,GINFO

3 Prime minister Water management Monthly Prescriptive Deep Learning FTP 450TB สสนก, RID,WaterResource

Data Visualization Data Science Data Engineer

1. Plan

2. Execute

Data Visualization SLA Data Science SLA Data Engineer SLA

สาํคญั

40

Big Data Maturity Model

41


BusinessMonitoringReport

BusinessInsights

BusinessOptimization

All Transaction LogsMonitoring andSummary

Integrate Social Data forBetter Insights

Real-time Data Feed:IoT and Real-timeOperation Actions

42



BusinessInsights





Business Monitoring ReportMine all the transactional dataat the lowest levels of detail

43



BusinessInsights





Business Monitoring ReportMine all the transactional dataat the lowest levels of detail

Business InsightsIntegrate unstructured datawith detailed structured(transactional) data to providenew metrics and newdimensions against which tomonitor and optimize keybusiness processes.

44



BusinessInsights





Business Monitoring ReportMine all the transactional data at thelowest levels of detail

Business InsightsIntegrate unstructured data withdetailed structured (transactional)data to provide new metrics andnew dimensions against which tomonitor and optimize key businessprocesses.

Business OptimizationLeverage real-time (or low-latency)data feeds to accelerate theorganization's ability to identify andact upon business and marketopportunities in a timely manner.

45



BusinessInsights


DataMonetization

BusinessMetamorphosis




Data as a Service:Creating Revenue fromData by Exchange orTrade

Artificial Intelligencefor BusinessSustainability,Value-Set, Passion:TransformingBehavior,Relationship, Culture, Ecosystem

46


Integrate predictive analytics into your key business processes to uncoverinsights buried in the massive volumes of detailed structured and unstructureddata. (Note: having business users slice and dice the data to uncover insights

worked fine when dealing with gigabytes of data, but doesn't work whendealing with terabytes and petabytes of data.) 47


Driving new business models, new processes, more meaningful business interactions,innovation, improved and faster decision making, and a more agile organization

A digital ecosystem is a business community of organizations and individuals transactingacross a distributed, adaptive, open, social, technical system with collaboration,transparency, constant evolution, self-organization, scalability and sustainability. 48

Big Data Governance

49

Data Governance

Data governance is the specification ofdecision rights and an accountabilityframework to encourage desirablebehavior in the valuation, creation, storage,use, archival, and deletion of data andinformation.• common data definition• data standard format• data integration strategy

50

Big Data Governance

Tom Plunkett; Brian Macdonald 51

Team working

Organization

Direction

Discovering the Data

52

Operation Team

Head of Business Units

Executives

Discovering the Data

Master Data

Executive Decision Data

Transactional Data

53

Big Data Governance WorksheetNo.

Type of Data(Master/Transactional/SummaryData)

DataName

Owner Used byCriticalBusinessService (Y/N)

Volume(MB/GB/TB)

Varieties ofTypes(Text, XML,JSON, Image,Sound, VDO,etc.)

Velocity(How fastdatachange inminutes)

ChangeControl(Y/N),ChangeProcedure

CurrentIssues

54

Business Analytics และ Business Intelligence



RetiredServices




Cloud

Data Monetization


IoT, Smart Devices


Smart Workforce




Vision,Mission

StatementsBusinessAnalytics

BusinessIntelligence

• What will happen?• What if and Why did it happen?• Predictive Modeling• Simulation/Optimization• Advanced Statistic Models• Data Mining (Text, Multimedia)• Data Science

• Who did that task?• What happened?• Dashboards, Alerts• Scorecards

Monitoring• Slice & Dice,

Drilling• Reports

• Data Lake• DWH



55

Thank you.

56

The Essential of Data Insights for Executives¸›าฐกถา 3 The Essential of... · The...

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Transcript of The Essential of Data Insights for Executives¸›าฐกถา 3 The Essential of... · The...