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Next Generation Big Data BI
STANLEY WANG SOLUTION ARCHITECT, TECH LEAD @SWANG68 http://www.linkedin.com/in/stanley-wang-a2b143b
What is Business Intelligence?
Improving organizations by providing
business insights to all employees leading to
better, faster, more relevant decisions
• Business Intelligence is the processes, technologies, and tools that help organization change data into information, information into knowledge and knowledge into plans that guide organization.
• Collections of technologies and approaches for gathering, storing, analyzing and providing access to data to help enterprise users make better business decisions.
• Dashboards • KPI • OLAP • Forecasting • Reporting
• BI dashboards Provide a customized snapshot of daily operations, and assist the user in identifying problems and the source of those problems, as well as providing valuable, up-to-date information about financial results, sales and other critical information – all in one place
Components of Business Intelligence • Key Performance Indicators Provide simplified KPI management and tracking with powerful features, formulae and expressions, and flexible frequency, and threshold levels. This module enables clear, concise definition and tracking of performance indicators for a period, and measures performance as compared to a previous period. Intuitive, color highlighters ensure that users can see these indicators in a clear manner and accurately present information. Users can further analyze performance with easy-to-use features like drill down, drill through, slice and dice and graphical data mining • Graphical Reporting Deliver web-based BI reports to anyone (or everyone) in the organization within minutes! The BI suite is simple to use, practical to implement and affordable for every organization. With our BI reporting and performance reporting module, you just point-and-click and drag-and-drop and you can instantly create a report to summarize your performance metrics, or operational data
• Graphical OLAP Makes it easy for users to find, filter and analyze data, going beyond numbers, and allowing users to visualize the information with eye-catching, stunning displays, and valuable indicators and gauges, charts, and a variety of graph types from which to choose
• Prediction and Forecasting Use historical product, sales, pricing, financial, budget and other data, and forecasts the measures with numerous time series options, e.g., year, quarter, month, week, day, hour or even second to improve your planning process
Traditional BI Architecture
BI platform:
Report
OLAP
Dashboard
KPIs
Charts
Data Mining
GEO-referenced analysis
Free Inquiry (QbE)
Collaboration
ETL
Enterprise level
Integration platform (not a closed product)
Multi engine (also mixing OS and proprietary)
Scalability
Security and visibility
BI Analytical Model
Analytical Model
BI Graphical Reports
BI Dashboard Documents
What Big Data Intelligence Looks Like?
When BI meets Big Data? • BI with Big Data delivers greater acuity, deeper insight and
smarter focus; • BI with Big Data leads to a proliferation of market
projections and forecasts;
Big Data Drive for Deeper Understanding
The Evolution of Business Intelligence
Big Data:
Batch Processing & Distributed Data Store
Hadoop/Spark; HBase/Cassandra
BI Reporting OLAP &
Data Ware House
Business Objects, SAS, Informatica, Cognos
Interactive Business Intelligence &
In-memory RDBMS QliqView, Tableau, HANA
Big Data:
Real Time & Single View
Graph Databases
1990’s 2000’s 2010’s
Speed
Scale
Scale
Speed
Business Intelligence Classifications
Traditional Analytics 1st Generation Analytics (Query & Reporting)
2nd Generation Analytics (OLAP, Data Warehousing)
Advanced Analytics/Optimization Rules
Predictive Analytics
Real-time and traditional Data Mining
Stream Analytics* Real-time, continuous, sequential analysis
(ranging from basic to advanced analytics) * In line of stream analytics, “embedded analytics,” although architecturally
different, could potentially play the same role
3rd-Generation BI
Legacy BI
“New Traditional” Analytics “2.5-Gen” Analytics (In-Memory OLAP, Search-Based)
Business Intelligence Use Cases
Traditional Analytics 1st Generation Analytics (Query & Reporting)
2nd Generation Analytics (OLAP, Data Warehousing)
Advanced Analytics/Optimization Rules
Predictive Analytics
Real-time and traditional Data Mining
Stream Analytics* Real-time, continuous, sequential analysis
(ranging from basic to advanced analytics) * In lieu of stream analytics, “embedded analytics,” although architecturally
different, could potentially play the same role
“New Traditional” Analytics “2.5-Gen” Analytics (In-Memory OLAP, Search-Based)
Example Target Solutions:
Fraud Detection / Risk
CRM Analytic
Supply Chain Optimization
RFID / Spatial Data
Other High-Volume
Focus on what is
happening RIGHT NOW
Real-Time Threshold
Focus on what will
happen
Analytic applications that
apply statistical
relationships in the form
of RULES
Focus on what did
happen
Turning data into
information is limited by the
relationships which the
end-user already knows to
look for.
Data mining to determine
why something
happened by unearthing
relationships that the
end-user may not have
known existed.
Modern Big Data BI Reference Architecture
A New BI Stack with Big Data
Ficus Big Data BI Architecture
Location Intelligence Engine
Social Business Intelligence