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