esf2.85 module 4 (bi)- lessons 1 & 2

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Introduction to Business Intelligence – Unit 4




Lesson 1

Introduction




Course Summary

• What is Business Intelligence (definitions), its background history and why is it used (including also military intelligence definition).

• Business Analytics and its difference towards Business Intelligence (BI).

• Different forms of organizational structures.




Course Summary

• The Benefits (Advantages) of BI• A list of all the benefits of BI to a Business

Organization, and possibly some drawbacks if it is misused.

• What is competitive intelligence?




Course Summary• Technologies used for BI (OLAP which stands for Online Analytical

Processing, Data Warehouses, Data Mining, Decision Support Systems and Decision Engineering, Digital Dashboard pages and KPI Lists, Statistical Analysis, Forecasting, Benchmarking, Quick Reporting, Measurement and the more modern technologies, such as the Cloud Computing and its SaaS, SOA-BI, and real time BI Analytics).

• Tools used for BI (the ETL tool by the SSIS, OLAP cubes and SSRS reports all created by Visual Studio, Microsoft products such as Excel, Visio, and Sharepoint, Microsoft BI tools such as the already mentioned Visual Studio, Silverlight and Microsoft.Net, plus some reference to other tools such as ActiveReports, Oracle BI, the IBM Analytics and Cognos, Pentaho, Palo for OLAP, Jaspersoft, Spago BI, and Eclipse BIRT Project).




Course Summary

• Some reference to some methodologies in use for BI (such as Agile BI, MIKE 2.0, and Rapid Implementation BI).

• User Aspect (and User Support), Market Aspect and Industry Aspect.

• Structured, semi-structured and unstructured data.




Course Summary

• How to manage information and transfer it in the most effective way, even with examples of some of the most popular Software application.

• Lastly, some references to Soft Skills used in BI departments, such as communicating the terminology.




• What is Business Intelligence ?– What is DATA? – What data do companies have access to?– How do companies make use of data?

• Military intelligence – characteristics -> accurate, timely information that can help produce

an effective strategy – very important today than ever before.

• As organisations continue to pursue their goals in an economy that seems more like a battlefield, it’s no wonder that they, too, feel the need for reliable information based on real and readily usable data – business intelligence.




• What is Business Intelligence (BI)?– BI - refers to skills, technologies, applications and practices

used to help a business acquire a better understanding of its commercial context.

Source: WikiPedia, http://en.wikipedia.org/wiki/Business_intelligence

• Business intelligence (BI) is defined as the ability for an organization to take all its capabilities and convert them into knowledge, ultimately, getting the right information to the right people, at the right time, via the right channel.

• Understanding the past… and predicting the future!




Other Definitions• Business Intelligence has become the vendors’ reference

to Decision Support, which on its turn, is defined as a system designed to facilitate business end users performing computer generating analyses of data on their own.

• Business Intelligence allows you to better understand, analyze, and predict what’s occurring within your company.

• Business Intelligence is the system or systems driving better Business Performance for companies with changing needs




• Business Intelligence is used for– Understanding business through collected data– Answering questions such as:• Which Of Our Customers Are Most Profitable?• Where Are Our Most Profitable Customers?• Who Are Our Customers?• Which Products Cost The Most To Maintain?• Where Can We Cut Costs?




Historical background• In a 1958 article, IBM researcher Hans Peter Luhn used the

term business intelligence. He defined intelligence as: "the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal."

• Business intelligence as it is understood today is said to have evolved from the decision support systems which began in the 1960s and developed throughout the mid-1980s.

• DSS originated in the computer-aided models created to assist with decision making and planning.

http://en.wikipedia.org/wiki/IBM

http://en.wikipedia.org/wiki/Hans_Peter_Luhn

http://en.wikipedia.org/wiki/Decision_making




• From DSS, data warehouses, Executive Information Systems, OLAP and business intelligence came into focus beginning in the late 80s.

• In 1989, Howard Dresner (later a Gartner Group analyst) proposed "business intelligence" as an umbrella term to describe "concepts and methods to improve business decision making by using fact-based support systems."

• It was not until the late 1990s that this usage was widespread.

http://en.wikipedia.org/wiki/Data_warehouse

http://en.wikipedia.org/wiki/Executive_Information_System

http://en.wikipedia.org/wiki/Online_analytical_processing

http://en.wikipedia.org/wiki/Gartner_Group




• Business Analytics vs Business Intelligence ?




• There are two things worth differentiating:• The first is the business aspect of BI — the need to get the most

value out of information. – This need hasn’t really changed in over fifty years (although the increasing

complexity of the world economy means it’s ever harder to deliver). And the majority of real issues that stop us from getting value out of information (information culture, politics, lack of analytic competence, etc.) haven’t changed in decades either.

• The second is the IT aspect of BI — what technology is used to help provide the business need. This obviously does change over time — sometimes radically.

• The problems in nomenclature typically arise because “business intelligence” is commonly used to refer both of these, according to the context, thus easy to confuse everyone.

http://timoelliott.com/blog/2011/03/why-the-last-decade-of-bi-best-practice-architecture-is-rapidly-becoming-obsolete.html




• Gathering intelligence, let alone using it! Takes time which is in short supply!!

• This is the era of strategic and unified views of business analytics for value creation.

• In times of rapid change and growing complexity, rapid learning becomes more valuable.

• How businesses make decisions using huge, noisy, messy data requires business analytics.




• It starts with an analytical view of data—what are you measuring and are you measuring what matters? Measurement (data generation and collection) is itself a process—the process of manufacturing an asset.

• When data is viewed this way, the analytical concepts of quality improvement and process optimization can be applied.




• The questions that need to be raised are: ‘‘What are you doing with your data? How are

people in your organization armed to make better decisions using the data, processes, and analytical methods available?’’

• Business analytics as portrayed by these analytical thinkers is about value creation.




• Value creation can take different forms through greater efficiency or greater effectiveness. Better decisions to reduce costs, reveal opportunity, and better allocate resources can all create value.

In this unit, we will learn about valuable business intelligence/ analytics foundational concepts to help organizations create value in a sustainable and scalable way.




• Companies & Corporations – Organisational Structure– Organizational structure refers to both the formal and informal

frameworks that shape how a business is operated. An organization’s structure determines how employees are grouped together and plays a large role in a firm’s success.

– Choosing a structure is not a one-size-fits-all decision, and business owners must select the model that best suits the needs of their organization.




• Functional Structure– In a functional structure, employees that perform similar tasks and hold similar positions

are grouped together into departments. Examples of functional departments include marketing, sales, human resources and production. Functional organizations have many advantages in the areas of coordination and motivation, people grouped together according to similarities in their positions can easily communicate and share information with each other.

– Functional organizations may suffer from interdepartmental conflict, and achieving effective communication between departments that each perform independent functions can prove difficult.




• Divisional Structure– The most common divisional structures group employees together by product, market

served or geographic location. Within this type of organization, each division is self-contained and has its own set of departments grouped by function. For example, instead of one central human resources department for the entire organization, each division instead has access to a human resources department that serves only that group. Divisional organizations benefit from the focus on individual environments but suffer from the duplication of some tasks and activities.




• Matrix Structure– A matrix organization has features of both the functional and divisional structures and is

perhaps the most complex. A matrix structure groups employees into project teams containing people from different functional areas of the business; they generally have to report to more than one supervisor. Matrix organizations choose team members based on the needs of the project, with the teams benefiting from the different viewpoints and skill levels. Matrix organizations may struggle with role and authority conflicts.




• Newer Forms– As the world around us changes, so must the business environment. Many organizations

now utilize relatively new structures to keep up with ever-changing needs. The flat organization, also referred to as a horizontal structure, exists when there are few or no hierarchical levels between employees and supervisors. Staff and management work together to make the decisions in this type of organization.

Virtual organizations – operate primarily via electronic communications. They require minimum face-to-face

contact, if any, and benefit from lower overhead costs than comparable brick-and-mortar firms.

• Effect on Organizational Culture– An organization’s structure and its culture are very much intertwined. An organization’s

culture can best be described as a collective personality represented by a shared set of experiences and values. Structure shapes not only how groups are formed, but also the behavior, attitudes and relationships of those groups.




• VIDEO: Corp 101_ The Basics of Corporate Structure




Lesson 2

Competitive Intelligence, the Benefits of Business Intelligence and Data Warehouses




• Competitive intelligence– the action of defining, gathering, analyzing, and

distributing intelligence about products, customers, competitors and any aspect of the environment needed

– to support executives and managers in making strategic decisions for an organization

• BI has internal focus and CI external focus




– Though the term business intelligence is sometimes used as a synonym for competitive intelligence, because they both support decision making,

– BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors.

• Business intelligence understood broadly can include the subset of competitive intelligence.

http://en.wikipedia.org/wiki/Competitive_intelligence




The Benefits of BI for Organizations• Eliminate guesswork• Get faster answers to your business questions• Get key business metric reports when and where

you need them• Get insight into customer behaviour• Identify cross-selling and up-selling opportunities




Benefits of BI for Organizations (2)• Learn how to streamline operations• Improve efficiency• Learn what your true manufacturing costs are• Manage inventory better• See where your business has been, where it is

now and where it is going




Drawbacks of BI (if misused)

• Piling of Historical Data• Cost (can be very high)• Complexity (that it can make an organization very

rigid)• Muddling of commercial settings• Limited use (especially to medium and small sized

industries)• Time consuming implementation




• Jack Welch, the chairman and CEO of General Electric from 1981–2001, once said that he measures everything.

• From a BI perspective, this is a great practice; BI is, at its root, a measurement system. But everything? How do you go about such an enormous task?




• Introduce group assignment work:– Case studies should include the Company Background: – Size of company in terms of sales and profits – Major products the company sells – General characteristics of their customers – Organizational chart--who does the CIO report to? – How many people work for the IT organization?

• Other potential ideas for the presentation:– A brief overview or demonstration of Business Intelligence software (10 minutes or less) – Major BI suppliers (products, services, revenues, profits) – The group should end the presentation on best practices for creating effective Business

Intelligence systems, then map how your cases fit into best practices. This is essentially a cross-case comparison that integrates r primary (case study) and secondary (journal articles & books) research.




• An overview of the BA Model• Information requirements move from the business driven environment down to

the technically oriented environment• The subsequent information flow moves upward from the technically oriented

environment toward the business-driven environment• There are many competencies, people, and processes involved in the creation of

BA.– Management specifies or develops an information strategy based on the company’s

business strategy– Operational decision makers need information and knowledge that supports the

company’s chosen strategy– Controllers and report developers create the information and knowledge to be used by

the company’s operational decision makers– In the technical environment, data warehouse, the specialist or the ETL (extract,

transformation, load) developer merges and enriches data, and makes it accessible to the business user.

– The business’s primary data generating source systems are run and developed by the IT professionals from IT operations and development.




• Often BI applications use data gathered from a data warehouse or a data mart. However, not all data warehouses are used for business intelligence, nor do all business intelligence applications require a data warehouse.

• In order to distinguish between concepts of business intelligence and data warehouses, Forrester Research often defines business intelligence in one of two ways:– Using a broad definition: "Business Intelligence is a set of methodologies,

processes, architectures, and technologies that transform raw data into meaningful and useful information used to enable more effective strategic, tactical, and operational insights and decision-making.“

– Forrester defines the latter, narrower business intelligence market as "referring to just the top layers of the BI architectural stack such as reporting, analytics and dashboards."

http://en.wikipedia.org/wiki/Data_warehouse

http://en.wikipedia.org/wiki/Data_mart

http://en.wikipedia.org/wiki/Forrester_Research

http://en.wikipedia.org/wiki/Dashboards_(management_information_systems)




• When using this definition, business intelligence also includes technologies such as data integration, data quality, data warehousing, master data management, text and content analytics, and many others that the market sometimes lumps into the Information Management segment.

• Therefore, Forrester refers to data preparation and data usage as two separate, but closely linked segments of the business intelligence architectural stack.

http://en.wikipedia.org/wiki/Information_Management




Data Warehouses

• A data warehouse is a database that stores current and historical data of potential interest to managers throughout the company.

• Data originate in many core operational systems and external sources, including Web transactions.

• The systems include legacy systems, RDBMS (Relational Database Management Systems), OODBMS (Object Oriented Database Management Systems), and systems based even on Web Files such as HTML or XML documents.




Data Warehouses

• Data from diverse applications are copied into the data warehouse database as often as needed – hourly, daily, weekly, monthly etc.

• The data are standardized into a common data model. Afterwards, they are consolidated so that they can be used across the enterprise for management analysis and decision making.

• Data is accessible and available to anyone as needed. However rights are sometimes used as to who access the data. Data cannot be altered from a data warehouse.




Data Warehouses

• A data mart is a subset of a data warehouse in which a summarized or highly focused portion of the organization’s data is placed in a separate database for a specific population of users.

• Datamining uses a variety of techniques to find hidden patterns and relationshipin large pools of data and infer rules from them that can be used to predict future behaviourand guide decision making. (Hirji, 2001).

• It helps companies engage in 1-1 marketing where personalized or individual messages can be created based on individual preferences.

• We will delve in detail into these 2 topics later on, together with the technique ETL used on datawarehouses (Extract, Transform and Load).




Data Warehouses

esf2.85 module 4 (bi)- lessons 1 & 2

Documents

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cohesion policy

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benefits of bi

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spago bi

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