Business Intelligence Overview

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Blue BI Business Intelligence Workshop Claudio Menozzi (BI overview reduced version for slideshare ) December 2014 Blue BI Business Intelligence

Transcript of Business Intelligence Overview

Page 1: Business Intelligence Overview

Blue BI

Business Intelligence Workshop

Claudio Menozzi

(BI overview – reduced version for slideshare)

December 2014

Blue BIBusiness Intelligence

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Agenda

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What is Business Intelligence? 1

BI Market Analysis3

Enabling BI: Datawarehouse technology4

BI output samples2

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Business Intelligence Definitions

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Business intelligence (BI) is the set of techniques and tools for the transformation of raw data into meaningful and useful information for business analysis purposes.

- Wikipedia

The BI and analytics platform market is in the middle of an accelerated transformation from BI systems used primarily for measurement and reporting to those that also support analysis, prediction, forecasting and optimization.

- Gartner - 2014

From Data to Knowledge to Action

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Data Availability

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Capabilities

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BI historical functionalities set

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BI Evolution: Data Visualization

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BI Evolution: Prescriptive and Predictive Analysis

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Fonte: Wikipedia

Predictive analytics answers the question what will happen. This is when historical performance data is combined with rules, algorithms, and occasionally external data to determine the probable future outcome of an event or the likelihood of a situation occurring.

The final phase is prescriptive analytics, which goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and showing the implications of each decision option.Prescriptive analytics not only anticipates what will happen and when it will happen, but also why it will happen.

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From BI to Business Enabling

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Agenda

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What is Business Intelligence? 1

BI Market Analysis3

Enabling BI: Datawarehouse technology4

BI output samples2

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Reporting

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Analytical Reporting: Olap Analysis

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Balance Scorecard/Dashboards

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The balanced scorecard is a strategic planning and management system that is used extensively in business and industry, government, and nonprofit organizations worldwide to align business activities to the vision and strategy of the organization, improve internal and external communications, and monitor organization performance against strategic goals.

- Balance Scorecard Institute

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Balance Scorecard

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Dashboards

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Data Visualization (1)

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Data Visualization (2)

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Agenda

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What is Business Intelligence? 1

BI Market Analysis3

Enabling BI: Datawarehouse technology4

BI output samples2

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Business Intelligence functionalities

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Information Delivery• Reporting:

Provides the ability to create highly formatted, print-ready and interactive reports• Dashboards:

A style of reporting that graphically depicts performances measures. • Ad hoc report/query:

Enables users to ask their own questions of the data, without relying on IT to create a report. • Microsoft Office integration:

MS Suite acts as the reporting. Advanced integration includes cell locking and write-back.• Mobile BI:

Enables organizations to develop and deliver content to mobile devices

Fonte: Gartner - 2014 Gartner Magic Quadrant for Business Intelligence and Analytics Platforms

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Business Intelligence functionalities

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Information Delivery• Reporting:

Provides the ability to create highly formatted, print-ready and interactive reports• Dashboards:

A style of reporting that graphically depicts performances measures. • Ad hoc report/query:

Enables users to ask their own questions of the data, without relying on IT to create a report. • Microsoft Office integration:

MS Suite acts as the reporting. Advanced integration includes cell locking and write-back.• Mobile BI:

Enables organizations to develop and deliver content to mobile devices

Fonte: Gartner - 2014 Gartner Magic Quadrant for Business Intelligence and Analytics Platforms

Analysis• Interactive visualization:

Enables the exploration of data via the manipulation of chart images,• Search-based data discovery:

Applies a search index to structured and unstructured data sources• Geospatial and location intelligence:

Specialized analytics and visualizations that provide a geographic, spatial and time context. • Embedded advanced analytics:

Enables users to leverage a statistical functions library embedded in a BI server. • Online analytical processing (OLAP):

Enables users to analyze data and navigate multidimensional drill paths.

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Business Intelligence functionalities

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Advanced BI Functionalities• Scorecard:

Scorecards are primarily delivered by corporate performance management.• Predictive Analysis:

Encompasses a variety of statistical techniques from modeling and data mining that analyze current and historical facts to make predictions about future, or otherwise unknown, events. • Prescriptive Analysis:

Enables users to ask their own questions of the data, without relying on IT to create a report.

Fonte: Gartner - 2014 Gartner Magic Quadrant for Business Intelligence and Analytics Platforms

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What BI for end-users?

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Gartner Analysis

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Business Intelligence and Analytics Platforms Advanced Analytics Platforms

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BI market trends

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Fonte: Gartner

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Agenda

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What is Business Intelligence? 1

BI Market Analysis3

Enabling BI: Datawarehouse technology4

BI output samples2

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Datawarehouse Definition

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Data warehousing incorporates data stores and conceptual, logical, and physical models to support business goals and end-user information needs.

A data warehouse (DW) is the foundation for a successful BI program.

Creating a DW requires mapping data between sources and targets, then capturing the details of the transformation in a metadata repository. The data warehouse provides a single, comprehensive source of current and historical information.

- TDWI (The Data Warehousing Institute)

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Datawarehousen architecture overview

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Datawarehouse Components• Data Integration• Quality Management• Master Data Management

DWH Tasks• Aggregate and homogenize

Data• Enable Historical Data• Data Integrity• Data Cleaning

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Datawarehouse definition by Bill Inmon

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A data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management's decision making process.

Subject-Oriented: A data warehouse can be used to analyze a particular subject area. For example, "sales" can be a particular subject.

Integrated: A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product.

Time-Variant: Historical data is kept in a data warehouse. For example, one can retrieve data from 3 months, 6 months, 12 months, or even older data from a data warehouse. This contrasts with a transactions system, where often only the most recent data is kept. For example, a transaction system may hold the most recent address of a customer, where a data warehouse can hold all addresses associated with a customer.

Non-volatile: Once data is in the data warehouse, it will not change. So, historical data in a data warehouse should never be altered.

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Gartner analysis: Data Integrator Tools

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Data acquisition for business intelligence (BI), analytics and data warehousing —Extracting data from operational systems, transforming and merging that dataConsolidation and delivery of master data in support of master data management (MDM) — Enabling the consolidation and rationalization of the data representing critical business Data migrations/conversions —replacement of legacy applications during mergers and acquisitions.Synchronization of data between operational applications — ensure database-level consistency across applications, both on an internal and an interenterprise basis Interenterprise data sharing — receive data from, external trading partners Delivery of data services in a service-oriented architecture (SOA) context — Data integration tools will increasingly enable the delivery of many types of data services.Integration involving cloud-based data — Integrating a combination of data residing on-premises or in SaaS applicationsBig data initiatives — Supporting delivery of data to, and accessing data from

Fonte: Gartner - 2014 Gartner Magic Quadrant for Data Integrator tools