POWER OF INTELLIGENCE AGILE BUSINESS DECISION MAKING
• Introducing Pieter Rambags • Introducing Nippur • Business Intelligence • Traditional • Active BI • Big Data
• The extended enterprise revisited • Conclusions
Nippur improves decision making
capability of customers
not incidentally but structurally
Services
BI strategy services
Business Intelligence services
Data warehousing services
Master data management
services
Business Intelligence – more than only IT
BI as process:BI is the continuous process allowing organizations to collect, register, analyze and apply information and knowledge in decision making to enhance the organization’s performance
BI as technology:
BI is the collection of ICT-tools that supports and shapes BI as process in organizations
BI as phenomenon or discipline:
BI is the whole of concepts, processes, strategies, culture, structure, methods, standards and ICT-means that allow organizations to behave more intelligent and to develop
themselves.
The BI information pyramid
Dashboards and standard reports
Adhoc querying and analysis Operational reporting Strategic Tactical Operational
+
+
• Business models change overnight
• IT in many cases not capable to meet Business data and information demands • Increase in data volume, speed and complexity
• Thus need for agile architectures providing data and information fast • Ability of the business to analyse the data themselves
• Availability of ‘Data Scientists’
Increase in (need of) Self Service BI
Business Intelligence – from an architectural perspective
Data Warehouse
Semantic integration Further aggregation &
BI reference model
SCHEDULING AND MONITORING
SOURCES
EXTRACT
/ L
OAD
STAGING DATA WAREHOUSE DATAMARTS
METADATA EXTRACT / L OAD ETL AGGREGATION + FIL TER APPLICATIONS
PROCESS SCHEDULING AND MONITORING ACCESS & USAGE MONITORING ETL
REPOSITORY
DATA MODELS REPOSITORYDBMS DEFINITIONSKPI DEFINITIONSREPORT MONITORINGPROCESS ACCESS ANDUSAGE
BUSINESS RULES SOURCE DATAVAULT BUSINESS DATAVAULT END USERS PRESENTATION PORTAL Trends: - Architecture generation - Architecture virtualization
Business Intelligence trends toward active
BI
Level 1: What happened?
• Standard reports
• Focus on availability and reliability of data
Level 2: Why did it happen?
• Standard reports as starting point for advanced analytics • Focus on finding relations in data
Level 3: What will happen next?
• Analysis of cause and effect relationships • Focus on building predictive business models
Level 4: What should I do?
• BI to support operational and tactical decisionmaking • Focus on application of predictive business models
Level 5: Automation
• BI supporting operation
The future, Level 5: Automation
17-6-2015 Creating Clarity 17
• NPS measurement versus social media sentiment analysis
• Social media data collected from 400.000(!) web sources in Dutch • Emailmatching of internal NPS data with social media data
• Conclusions:
• NPS shows higher satisfaction ratios
• Significant and relevant relationship between NPS measurement and data mining effort
• Data mining automation can replace NPS measurement at lower cost
• Crimewatch monitor of Algemeen Dagblad
• showing decrease in crime over the years
• However feeling of insecurity seems to increase
• Research
• Data mining of textual data on more advanced sentiments • Feeling insecure
• Anger • Frustration • ….
• Results expected september 2015
• Data privacy versus data usage: a paradigm shift
Integrated architecture
Business
Model
The extended enterprise revisited
Communicati on model
Information Hub: a business service to integrate and
share information
People Territories Businesses Competitors Products Organizations Customers MarketsGovernance, Processes, technology
Business analytics Operational process monitoring Planning And budgetting Master Data sharing Ad-hoc Data discovery Live Dashboards Data Dictionary
Information Services
Information Services
Internal transaction sources Internal transaction sources Internal transaction sources Internal transaction sources Internal transaction sources Internal transaction sources Internal transaction sources External transaction sources DocumentsMD Authoring and Data governance Data Integration MetadataMgt. Data Quality Mgt. Data Warehousing. Master Data Mgt. Business analytics Operational process monitoring Planning And budgetting Master Data sharing Ad-hoc Data discovery Live Dashboards Data Dictionary
Future Reference Architecture
• Business Intelligence shifts from predicting the past to automating the future of decision making
• Architectures and technology support massive, high performance and near realtime data collection and decision making
• Solutions can be implemented at an ever faster pace • There truly is a data explosion taking place
• Big Data analytics looks promising but requires out-of-the-box thinking • Data privacy is an important topic to consider
• Sharing the power of knowledge could boost business productivity
• But are we ready and willing to share our knowledge and data?
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