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Danairat T.
อ.ดนยัรฐั ธนบดธีรรมจารี+668-1559-1446 Line ID: danairatFB: www.facebook.com/tdanairat
Part 1 Internet of ThingsPart 2 Digital Transformation Strategic Framework
- Steps of Digital Transformation- Business Service Analysis Worksheet- Enterprise Repository
Internet of ThingsThe Digital Transformation
Digital Initiatives
Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
CEO
CFO
COO
CMO
BigData
DigitalSecurity
“Innovation”
“Efficiency”
“Sustainability”
Cloud
D ata M onetization
NewCustomers,
Channels
IoT, Smart D evices
Business ProcessOptimization/Outsou
rcing
Smart Workforce
EnterpriseM etamorphosis
Digital Organization
Business Process as a ServiceM ore ControlM ore Flexible
Vis ion,M iss ion
Statements
The Digital Transformation Series
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Part 1
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ApplicationAreas
Smart Cities SmartEnvironment
SmartEnergy
SmartAgriculture E-Health Retail Logistics Industrial
Control
Internet of Things
Monika, 2015 3
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• The Internet of Things (IoT) is the network ofphysical objects that contain embedded technologyto communicate and sense or interact with theirinternal states or the external environment.
What is IoT?
http://www.gartner.com/it-glossary/internet-of-things/
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IoT Architecture
https://techbeacon.com/4-stages-iot-architecture
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• IoT has evolved from the convergence of– Wireless technologies– Micro-electromechanical systems (MEMS)– Microservices– Internet
IoT Technologies
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Wireless Technologies (1)WiFi
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Wireless Technologies (2)WiMAX
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Bluetooth technology
http://stg.dotemirates.com/ar/details/3932968?from=dot
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IoT Wireless Technology
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• Performance– Low Bandwidth– High Error Rate
• Security– Broadcast signal– Easy to be interfered by other sources
Issues of Wireless Technology
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Wireless Technology SummaryBa
ndw
idth
Range
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MicroElectroMechanical System(MEMS) (1)
• A MEMS(microelectromechanicalsystem) is a miniaturemachine that has bothmechanical and electroniccomponents.
• The physical dimension ofa MEMS can range fromseveral millimeters to lessthan one micrometer.
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• The functional elements ofMEMS are miniaturizedstructures, sensors,actuators, andmicroelectronics.
• The most notable elementsare the microsensors andmicroactuators.
MicroElectroMechanical System(MEMS) (2)
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• Microservice architecture - is a variant of the service-oriented architecture (SOA) architectural style thatstructures an application as a collection of loosely
coupled services.• Services should be fine-grained and
the protocols should be lightweight.
MicroServices (1)
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MicroServices (2)
MicroServices Architecture Pattern
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MicroServices (3)
MicroServices Architecture Pattern
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TCP/IP Stack
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IoT Stack
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IoT Example Cases
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New Digital Touch PointsNot only application software
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Smart Farming
Monika, 2015 22
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Drones will continue torevolutionize photographyand videography but real
innovation will derive fromutility in vertical
applications such asdelivery, care, exploration,
etc.
Image Credit: Alec Momont 23
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Mixed Reality
Image via MagicLeap
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3D Printing
suefeng.com/blog/3d-printing-and-additive-manufacturing/
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Smart Home
Monika, 2015 26
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Smart Cars
Monika, 2015 27
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Smart Healthcare
Monika, 201528
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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. Average householduses 300 products in a year
independent.co.uk
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Retails Store Use Cases
Store Layout ProfitsCustomer Density
independent.co.uk
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การเตอืนภยัพบิตั ิSensor ปรมิาณนําฝน นําในเขอืน ปรมิาตรเขอืน, แสดงแนวโนม้สภาวะนําทว่มNearly Real-Time
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Outbreak with Early Detection
Management of Outbreak with Early Detection
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Connected Health
ประชาชนแข็งแรง
รา้นขายยา
โรงพยาบาลและคลนีกิ
แนะนําออกกําลงักาย และการพกัผอ่น
การเลอืกซอืยา
ขอ้มลูสขุภาพและการรกัษา
อุปกรณ์ดา้นสุขภาพ
แบง่ปนัขอ้มูล รวดเร็วและปลอดภยั(Secure Speed Data Sharing)
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New Digital Touch PointsNot only application software
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Internet of Things
The internet of things (IoT) is the network of physical devices, vehicles, buildingsand other items—embedded with electronics, software, sensors, and networkconnectivity that enables these objects to collect and exchange data.
ITU. 26 June 2015.
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Part 2
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Digital Transformation Strategic Framework
Digital Initiatives
Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
CEO
CFOCOOCMO
Big Data DigitalSecurity
“Innovation”“Efficiency”
“Sustainability”
Cloud
Data Monetization
New Customers, Channels
IoT, Smart Devices
Business ProcessOptimization/Outsourcing
Smart Workforce
EnterpriseMetamorphosis
Digital Organization
Business Process as a ServiceMore ControlMore Flexible
Vision,Mission
StatementsBusinessAnalytics
BI
• 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
• DWH• Data Lake
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Information Technologyvs.
Digital Technology
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Big Data IntroductionVolume
Variety Velocity
DB TableDelimited Text
XML, HTML
Free Form TextImage, Music, VDO, Binary
Batch
Near real time
Real time
GB
TB
PB
XB
ZB
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Choosing between Business Intelligence (BI)and Business Analytics (BA)
While superficially similar, the difference between business intelligence vs businessanalytics 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 intelligencemay be an optimal solution.
- If you intend to change your business model and need to know where to start,business analytics might be the best option.
https://selecthub.com/business-intelligence/business-intelligence-vs-business-analytics/
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Choosing between Business Intelligence (BI)and Business 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 andbusiness intelligence can help you take your business where you want it to go.
https://selecthub.com/business-intelligence/business-intelligence-vs-business-analytics/
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Choose the Right Presentation Chart Types
http://img.labnol.org/di/data-chart-type.png 43
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Understand Enterprise AnalyticsNeeded Using Digital Transformation
Reference Model
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Digital Transformation Reference Model
“Innovation”“Efficiency”
“Sustainability”
Vision,Mission
Statements
Big Data DigitalSecurityCloud
Key Technologies for Digital Transformation
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Digital Transformation Reference Model
“Innovation”“Efficiency”
“Sustainability”
Vision,Mission
Statements
Anal
ytic
sIn
itiat
ives
?
Big Data DigitalSecurityCloud
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Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
Big Data DigitalSecurity
“Innovation”“Efficiency”
“Sustainability”
Cloud
Vision,Mission
Statements
1. (Re)Identifying your vision and missionsStrategic and Top Decision Making:-- Political and Policy Reports- Economic Reports- Customer Analytic Trends- Technology Trends- Economic Value
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Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
Big Data DigitalSecurity
“Innovation”“Efficiency”
“Sustainability”
Cloud
Vision,Mission
Statements
2. Identifying Business Services and Objectives
Business Services/Objectives:-- Social Listening Analytics- Customer Experiences / UX- Discover Unmanned Customers- Demographic Analytics- Voice of Customers- Objectives/Measurements
Results
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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.
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3. Identifying BI for Management Level
Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
CEO
CFOCOOCMO
Big Data DigitalSecurity
“Innovation”“Efficiency”
“Sustainability”
Cloud
Digital Organization
Vision,Mission
StatementsManagement BI:-• Promotion Impact Report• Channel Productivity• Operational Efficiency• Profit and Loss Report• Compliance Reports• Internal Policy Adoption
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Digital Organization
• CEO : combine all successes from all C-Level• CMO: innovation for new products offering• COO : operation and automation• CFO : finance, budgeting, HR, Audit, QA and IT• Put the right skill on the right role• Promote paperless policy organization
CEO
CFOCOOCMO
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Top Business Questions from CMO
CMO
Chief Marketing Officer (CMO), Innovation, Sales and Promotion:-• Which customers should we target?• What has caused the change in my pipeline?• Which are my most profitable campaigns/region?• Did store sales spike when we advertised in the local paper or
launched the campaign?• What is the most profitable sales channel and how has that
changed over time?
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Top Business Questions from COO
COO
Chief Operation Officer (COO):-• Lead time and cost of production for each products• Which order processing processes are most inefficient?• Which vendors are best at delivering on time and on
budget?–• How many additional personnel do we need to add per
branch?• Percent of error or defect trend for each product
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Top Business Questions from CFO
CFO
Chief Financial Officer (CFO):-• What is the fully loaded cost of new products
deployment?• What are the current trends in cash flow, accounts
payable and accounts receivable and how do theycompare with plan?
• What is the expected annual profit/loss based oncurrent marketing and sales forecasts?
• How are forecasts trending against the annual plan?
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Digital Initiatives
Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
CEO
CFOCOOCMO
Big Data DigitalSecurity
“Innovation”“Efficiency”
“Sustainability”
Cloud
Data Monetization
New Customers, Channels
IoT, Smart Devices
Business ProcessOptimization/Outsourcing
Smart Workforce
EnterpriseMetamorphosis
Digital Organization
Business Process as a ServiceMore ControlMore Flexible
Vision,Mission
Statements
4. Identifying Operational BI
Operational BI:-- Task Tracking Status- Alerts on Progression- Error correction and
recommendation
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BI and Alerts for Operational Level
• BI and alerts for customers need to be more flexible• BI and alerts for production operation team need to be more automation• BI and alerts for back office (HR, payroll, finance) need to be more
auditable
Digital Initiatives
Data Monetization
New Customers,Channels
IoT, Smart Devices
Business ProcessOptimization/Outsourcing
Smart Workforce
EnterpriseMetamorphosis
Business Process as a ServiceMore ControlMore Flexible
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Key Questions Type in each level of enterprise
Who
How
What
Why
When
Digital Initiatives
Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
CEO
CFOCOOCMO
Big Data DigitalSecurity
“Innovation”“Efficiency”
“Sustainability”
Cloud
Data Monetization
New Customers, Channels
IoT, Smart Devices
Business ProcessOptimization/Outsourcing
Smart Workforce
EnterpriseMetamorphosis
Digital Organization
Business Process as a ServiceMore ControlMore Flexible
Vision,Mission
Statements
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Digital Initiatives
Digital Platform
Business Services &Business Objectives
NewServices
OptimizedServices
RetiredServices
CEO
CFOCOOCMO
Big Data DigitalSecurity
“Innovation”“Efficiency”
“Sustainability”
Cloud
Data Monetization
New Customers, Channels
IoT, Smart Devices
Business ProcessOptimization/Outsourcing
Smart Workforce
EnterpriseMetamorphosis
Digital Organization
Business Process as a ServiceMore ControlMore Flexible
Vision,Mission
Statements
5. Identifying BI and BA Platform
BI &BusinessAnalyticsPlatforms :-• Traditional BI• Big Data• Cloud• Digital Security
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5.1 Traditional Data Warehouseand Business Intelligence
Platform
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Traditional Data Warehousing and Business Intelligence
Metadata and Logical Data Model / APIs
Data SourcesLayer
Foundation Layer Access LayerStaging Layer Presentation Layer
Data Marts
Operation Level
Management Level
Executive Level
Datawarehouse
Staging DB/ODSOLTP
OLAP
Data Mining
ETL ETL
Application 1
Application 2
DB or Files
Data Mart / Cube
DW Tools BI Tools
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Traditional Data Warehousing and Business Intelligence
Metadata and Logical Data Model / APIs
Data SourcesLayer
FoundationLayer
Access LayerStaging Layer Presentation Layer
Data Marts
Operation Level
Management Level
Executive Level
Datawarehous
eStaging DB/ODS
OLTP
OLAP
DataMining
ETL ETL
Application 1
Application 2
DB or Files
Data Mart / Cube
DW Tools BI Tools
1. Data Source Layer: definingwhich data will be loaded intothe system and analyzed.• Text Files• OLTP, Databases• XML• JSON• Spreadsheet Files
Source Dara Examples:-- Retail POS system- Web Site- DBMS
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Traditional Data Warehousing and Business Intelligence
Metadata and Logical Data Model / APIs
Data SourcesLayer
FoundationLayer
Access LayerStaging Layer Presentation Layer
Data Marts
Operation Level
Management Level
Executive Level
Datawarehous
eStaging DB/ODS
OLTP
OLAP
DataMining
ETL ETL
Application 1
Application 2
DB or Files
Data Mart / Cube
DW Tools BI Tools
2. ETL (Extract, Transform, and Load)and Staging Layer:
• Tools to move data to stagingDB
• Staging DB is a temporarystorage to be loaded to DWH
• Staging DB could beoperational reportingtool/platform
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Traditional Data Warehousing and Business Intelligence
Metadata and Logical Data Model / APIs
Data SourcesLayer
FoundationLayer
Access LayerStaging Layer Presentation Layer
Data Marts
Operation Level
Management Level
Executive Level
Datawarehous
eStaging DB/ODS
OLTP
OLAP
DataMining
ETL ETL
Application 1
Application 2
DB or Files
Data Mart / Cube
DW Tools BI Tools
3. Data Warehouse:-• Used for reporting• A scalable DB storing historical
enterprise data• Online Analytical Processing• Not used for transaction
processing
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Traditional Data Warehousing and Business Intelligence
Metadata and Logical Data Model / APIs
Data SourcesLayer
FoundationLayer
Access LayerStaging Layer Presentation Layer
Data Marts
Operation Level
Management Level
Executive Level
Datawarehous
eStaging DB/ODS
OLTP
OLAP
DataMining
ETL ETL
Application 1
Application 2
DB or Files
Data Mart / Cube
DW Tools BI Tools
4. Access Layer:-• Data Mart for business fast
query (Star Schema)• OLAP uses a
multidimensional datamodel, allowing forcomplex analytical and ad-hoc queries with a rapidexecution time
• Data mining for mostly instructured data format
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Traditional Data Warehousing and Business Intelligence
Metadata and Logical Data Model / APIs
Data SourcesLayer
FoundationLayer
Access LayerStaging Layer Presentation Layer
Data Marts
Operation Level
Management Level
Strategic Level
Datawarehous
eStaging DB/ODS
OLTP
OLAP
DataMining
ETL ETL
Application 1
Application 2
DB or Files
Data Mart / Cube
DW Tools BI Tools
5. Presentation Layer:-• Need to gather
requirements fromBusiness Units forVisualization and Touchpoints
• Need to identify datasources and method todeliver results
• Enterprise dashboards,reports and alerts thatpresent findings from theanalysis
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5.2 Big Data for BusinessAnalytics Platform
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Big Data for Business Analytics Platform
Big Data InfrastructureBig Data Infrastructure
Next BestAction BI/Report
Parallel Data Processing, Refinery
Ingestion and Acquisition
Distributed Data Store, Data Lake
Monitoring,Resource
Managementand Metadata
Framework
Security andControl
Framework
PredictiveAnalytics
Descriptive/Diagnose Analytics
PrescriptiveAnalytics
Big Data Platform
Big Data Applications
Compute Storage, Network
FraudAnalysis
CyberSecurity
TalentSearch
Staffs Managers PartnersCustomers ExecutivesExperts
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Big Data System Architecture
Storage Server and Network Infrastructure
NoSQL with Maps DB
Application ServerHadoop
HDFS, YARN, Spark, Storn, MRv2,Hive, Mahout, Zookeeper, Mesos,
Etc.
App1 ExecutiveReportsApp2 Advanced
Analytics
Syst
emM
onito
ring
Syst
emSe
curit
y
Physical Data Center
Access Channels
Staffs Partners ManagersCustomers Executives Experts
InfraPlatformAppsAccess68
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Block Size =64MB/128MB/256MBReplication Factor = 3
HDFS: Hadoop Distributed File System
Cost/GB is a few¢/month vs $/month
apache.org/hadoop/
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MapReduce: Distributed Processing
apache.org/hadoop/
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Descriptive/Diagnostic analytics
Descriptive/Diagnostic analytics answers the question, "What happened in thebusiness?" It looks at data and information to describe the current businesssituation in a way that trends, patterns and exceptions become apparent. Thistakes the form of reports, dashboards, MIS, etc.
mu-sigma.com
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Predictive analytics
Predictive analytics answers the question, "What is likely to happen in thefuture?" Here data modeling and forecasting are used to determine futurepossibilities
mu-sigma.com
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Prescriptive analytics
Prescriptive analytics is the combination of the above to provide answers to the"So what?" and the "Now what?" For example, what should a business do toretain key customers? How can businesses improve their supply chain to enhanceservice levels while reducing costs?
mu-sigma.com
Action!
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Big Data Maturity Model
BusinessMonitoringReport
BusinessInsights
BusinessOptimization
All Transaction LogsMonitoring and Summary
Integrate Social Data forBetter Insights
Real-time Data Feed:IoT and Real-timeOperation Actions
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Big Data Maturity Model
BusinessMonitoringReport
BusinessInsights
BusinessOptimization
All Transaction LogsMonitoring and Summary
Integrate Social Data forBetter Insights
Real-time Data Feed:IoT and Real-timeOperation Actions
Business Monitoring ReportMine all the transactional data at thelowest levels of detail
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Big Data Maturity Model
BusinessMonitoringReport
BusinessInsights
BusinessOptimization
All Transaction LogsMonitoring and Summary
Integrate Social Data forBetter Insights
Real-time Data Feed:IoT and Real-timeOperation Actions
Business Monitoring ReportMine all the transactional data at thelowest levels of detail
Business InsightsIntegrate unstructured data withdetailed structured (transactional) datato provide new metrics and newdimensions against which to monitorand optimize key business processes.
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Big Data Maturity Model
BusinessMonitoringReport
BusinessInsights
BusinessOptimization
All Transaction LogsMonitoring and Summary
Integrate Social Data forBetter Insights
Real-time Data Feed:IoT and Real-timeOperation Actions
Business Monitoring ReportMine all the transactional data at thelowest levels of detail
Business InsightsIntegrate unstructured data withdetailed structured (transactional) datato provide new metrics and newdimensions against which to monitorand optimize key business processes.
Business OptimizationLeverage real-time (or low-latency)data feeds to accelerate theorganization's ability to identify and actupon business and marketopportunities in a timely manner.
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Big Data Maturity Model
BusinessMonitoringReport
BusinessInsights
BusinessOptimization
DataMonetization
BusinessMetamorphosis
All Transaction LogsMonitoring and Summary
Integrate Social Data forBetter Insights
Real-time Data Feed:IoT and Real-timeOperation Actions
Data as a Service:Creating Revenue fromData by Exchange or Trade
Artificial Intelligence forBusiness Sustainability,Value-Set, Passion:Transforming Behavior,Relationship, Culture ,Ecosystem
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Big Data Maturity Model
Integrate predictive analytics into your key business processes to uncover insightsburied in the massive volumes of detailed structured and unstructured data. (Note:having business users slice and dice the data to uncover insights worked fine whendealing with gigabytes of data, but doesn't work when dealing with terabytes and
petabytes of data.)79
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Big Data Maturity Model
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.
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Big Data People and Team Structure
Big Data ProgramCommittee
ProjectManager
Big DataArchitect Data Scientist Business
Analyst
DataDataIntegrationSpecialist
Developer
Big Data Evangelist
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Big Data Team StructureNo. Roles Description1 Big Data
ProgramCommittee
The Team to develop Big Data initiative and deliver solutionresults
2 Big DataEvangelist
The business evangelist must have a combination of goodcommunication and presentation skills and deep contextualbusiness knowledge, as well as a clear understanding oftechnology in general and big data techniques.
3 ProjectManager
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 DataArchitect
The person who has background in parallel and distributedcomputing architecture. This person is knowledgeable aboutfundamental performance “gotchas” that will impede thespeed, scalability, and extensibility of any application requiringmassive data volumes.
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Big Data Team StructureNo. Roles Description5 Data
ScientistThe data scientist combines knowledge of computer science,the use of high-performance applications, and statistics,economics, mathematics, and probabilistic analysis skills.
6 BusinessAnalyst
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 DataIntegrationSpecialist
The person who has experience in data extraction,transformation, loading, and data transformations inpreparation for cleansing and delivery to target systems. Seekpeople with experience with data federation and virtualization,data quality, and metadata analysis.
8 ApplicationDeveloper
The technical resources with the right set of skills forprogramming and testing parallel and distributed applications.
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Big Data Project Life Cycle
Big DataPlanning
• Identify Targeted Users• Identify Target Opportunities
/ Key Measurements• Identify Data Sources/Types• Identify Data Capturing
Approaches• Identify Data Processing and
Visualization Planning• Identify Big Data Platform• Identify Security• Identify Governance and
Change Control for Operation• Identify Team Structure• Identify Phasing, Budget and
Cost
Big DataDevelopment
• Develop Use Cases• Develop Requirements
Definition• Develop Big Data Solution
Framework• Develop the Development
and Test Environment• Develop Data Capture• Develop Analytics• Integrate Visualization• Manage Assets and
Configurations
Operation andSupport
• Monitor Big Data PlatformAvailability, Utilization andCapacity Planning
• Manage Operation Tasks(Admin. Scripts,Commands), DataCapturing System,Upgrading or Patching
• Manage Service Requestsand Incidents
• System admin. Training• Helpdesk Training• End-User Training
(Analytic Results)
Evaluation
• Adoption Rates for eachanalytics results
• No. of Missing AnalyticResults
• No. of Missing Data• Lost hours per month• Avg. of each Analytic Result
Response Time• No. of Technology System
Failure per month• Evaluate Activity
Conformance with Policies
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No. Phases Activities People Deliverables
1 Planning Identify Targeted Users Big Data Program Committee Big Data DiscoveryWorksheet
2 Planning Identify Target Opportunities Big Data Program Committee Big Data DiscoveryWorksheet
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 TypesInformation
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 Frameworkand User InterfaceSummary
7 Planning Identify Big Data Platform Big Data Architect, Project Manager Big Data Platform Summary
8 Planning Identify Security Corporate Information Security, Big DataArchitect, Project Manager
Security Scope Summary
9 Planning Identify Governance andChange Control forOperation
Internal Control Team, CorporateInformation Security, Big Data Architect,Project Manager
Governance, RACI, ChangeProcedures Summary
10 Planning Identify Phasing Budget andCost
CIO, CFO, Project Manager, BusinessAnalyst
Project InvestmentSummary
Key Activities, People and Deliverables
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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 SolutionFramework
Big Data Architect Solution ComponentDiagram
4 Development Develop the Development andTest Environment
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 andVisualization Results
8 Development Manage Assets andConfigurations
Project Manager, Big Data Architect,Corporate Information Security, Head of ITOperation
Assets Inventory andConfigurations ChangeProcedure
Agile Methodology may apply in Big Data Development Phase.
Key Activities, People and Deliverables
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Key Activities, People and DeliverablesNo. Phases Activities People Deliverables
1 Operation andSupport
Monitor Big Data Platform Availability,Utilization and Capacity Planning
IT Operation Team Availability, Utilization andCapacity Planning Report
2 Operation andSupport
Manage Operation Tasks (Admin. Scripts,Commands), Data Capturing System,Upgrading or Patching
IT Operation Team, Big DataArchitect
Schedule or Ad-HocOperation Activities
3 Operation andSupport
Manage Service Requests and Incidents IT Operation Team Service Requests andIncidents Procedures
4 Operation andSupport
System Administration Training Big Data Architect,Data Integration Specialist,Developer, ITAdministration, ITOperation
System Administration andOperation Training Activity
5 Operation andSupport
Helpdesk Training IT Administration, ITOperation, IT Helpdesk
Helpdesk Training Activity
6 Operation andSupport
End-User Training (Analytic Results) Business Analyst, BusinessUsers
End-User Training Activity
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Danairat T.
Key Activities, People and Deliverables
No. Phases Activities People Deliverables
1 Evaluation Create Adoption Rates for eachanalytics Results
IT Operation Percent of user adoption
2 Evaluation Create No. of Missing AnalyticResults
Big Data Program Committee No. of Missing AnalyticsReport
3 Evaluation Create No. of Missing DataResults
Big Data Program Committee No. of Missing Data Report
4 Evaluation Create Lost hours per monthResults
Big Data Architect, Data Scientist,Data Integration Specialist
Lost hours per monthReport
5 Evaluation Create Avg. of each AnalyticProcessing and Response TimeResults
Data Integration Specialist, Data Scientist Analytic Processing andResponse Time Report
6 Evaluation Create No. of Technology SystemFailure per month Results
Business Analyst, Big Data Architect, DataScientist, Developer
Technology System Failureper month Report
7 Evaluation Evaluate Activity Conformancewith Policies
Big Data Architect, Project Manager Change Control Log Report
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Danairat T.
Digital Initiatives Worksheet
Service Name: Key Objectives:
Service Owner:
Version: Date/Time:
Critical Check Points, Evidences
Key Business Issues: Key Technology Issue:
1. ___________, __________2. ___________, __________3. ___________, __________4. ___________, __________5. ___________, __________
1. ___________2. ___________3. ___________4. ___________
NewImproveRetire
1. ___________2. ___________3. ___________4. ___________5. ___________
Lists of Stakeholders
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Danairat T.
The Big Data Governance WorksheetNo.
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
90
Danairat T.
อ.ดนยัรฐั ธนบดธีรรมจารี+668-1559-1446 Line ID: danairat
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