KORA. Business Intelligence An Introduction

Transcription

1 Business Intelligence An Introduction

2 Outline What is Business Intelligence Business Intelligence Market BI Tools & Users

3 What should be understood when someone uses the term Business Intellingence? But first, lets hear how it sounds to you

4 We know the meaning of Business but does the word Intelligence really mean Zeka in Turkish here?

5 What is Business Intelligence? Insight and foresight gained by analyzing large amounts of business data Gaining advanced knowledge about the business byözel analyzing Yazılım ve Danışmanlık enterprise Hizmetleri data, and using this knowledge to do a more effective and info@kora.com.tr profitable business

6 Some other BI definitions Business intelligence refers to the capability of providing a 360 view of the business. It provides a platform that enables decision-makers within an enterprise to have the latest competitive internal and external information at their finger tips in a clean, consistent and easy- to-use manner. Business intelligence refers to systems and technologies that provide the business with the means for decision-makers to extract personalized meaningful information Özel Yazılım about their ve Danışmanlık business and industry, Hizmetleri not typically available from internal systems alone. This includes advanced decision support tools andinfo@kora.com.tr back-room systems and databases to support those tools.

7 Gartner s BI Definition BI is a user-centered process that includes accessing, exploring and analyzing data and developing insights and understanding, which leads to improved and informed decision making. Özel Yazılım ve Danışmanlık Hizmetleri info@kora.com.tr

8 TDWI s view of Business Intelligence Wisdom Review, Measure, Refine Events Experience Act Rules and Plans Models Özel Yazılım ve Danışmanlık Hizmetleri Analytical Knowledge info@kora.com.tr Operational Systems Data Information Tools Data Warehouse

9 TDWI s view of Business Intelligence From Data to Information. More specifically, a data warehouse extracts data from multiple transaction or operational systems and integrates and stores the data. For example, a data warehouse might match and merge customer records from five operational systems (e.g. orders, service, sales, shipments, and loyalty programs) into a single file. This extraction and integration process turns data into a new product information From Information to Knowledge. Then, users equipped with analytical tools (e.g. query, reporting, OLAP, and data mining tools) access and analyze the information in the data warehouse. Their analysis identifies trends, patterns, and exceptions. Analytical tools enable users to turn information into knowledge. From Knowledge to Rules. Armed with these insights, users then create rules from the trends and patterns they ve discovered. These rules can be simple (e.g., Order 50 new units whenever inventory Özel falls Yazılım below 25 units. ) ve Danışmanlık They can be forecasts Hizmetleri or what if projections based on past trends and working assumptions. Or the rules can be highly complex, generated by statistical algorithms or models. For example, statistically-generated rules can dynamically configure prices in response to changing market conditions, optimize freight hauling schedules info@kora.com.tr a large carrier network, or determine the best cross-sell opportunities using customer response models.

10 TDWI s view of Business Intelligence Özel Yazılım ve Danışmanlık Hizmetleri info@kora.com.tr

11 Types of Decision Making Operational One system view Support the ongoing operational system Tactical Integrated view Intended for monitoring KPI Strategic Integrated view Measure Özel facts Yazılım overve longer Danışmanlık periodshizmetleri of time BI includes all levels of decision making!

12 Another View of BI Özel Yazılım ve Danışmanlık Hizmetleri

13 History of BI At one time, organizations solely depended on their IT departments to provide them with both standard and customized reports. This goes back to the days of mainframes and minicomputers, when most end users did not have direct access to the computers. This began to change in the 1970s, when online host-based systems entered the scene. Even then, these systems were used primarily for entering business transactions, and reporting capabilities were primarily a limited number of predefined reports. IT typically was overburdened, and users had to wait for days or weeks to get their reports if they needed reports other than the standard ones that were available. Eventually, Executive Özel Information Yazılım ve Systems Danışmanlık (EIS), and Management Hizmetleri Information Systems (MIS) which addressed the decision support needs of executives and managers, were developed. Still, these systems mostly ran on operational hardware and consisted of predefined screens and reports. info@kora.com.tr

14 History of BI cont. With the advent of the PC in the 80s, it became possible to take extracts from the operational databases and transfer these to the managers and analysts desktop. Basic BI tools (Spreadsheets, etc.) then gave users the technology to create their own basic routine and custom reports. Artificial Intelligence and Expert Systems also became popular in this timeframe. The 90s saw the surge of Data Warehousing and multidimensional analysis (OLAP) which meant that the extracted data was transferred to a separate server, got transformed and integrated. Client-server BI tools were developed to access and analyze this data. Data Mining was born and CRM became popular. The trends in the 2000s are: Özel Yazılım ve Danışmanlık Hizmetleri Thin client, zero footprint BI tools Dashboardswww.kora.com.tr Push BI into info@kora.com.tr every corner of the enterprise Real time BI Business Activity Monitoring (BAM) Corporate Performance Management (CPM)

15 History of BI cont. Özel Yazılım ve Danışmanlık Hizmetleri

16 So What Is BI? What is generally excepted as BI: Standard & Parameterized Reporting Ad-Hoc Query and Analysis Environments (Relational) OLAP Analysis (Multidimensional) Data Mining Dashboards Business ActivityMonitoring Alerting CorporateÖzel Performance Yazılım ve Danışmanlık Management Hizmetleri KPI Tracking Scorecards Data Quality Analysis and Data Cleansing

17 Özel Yazılım ve Danışmanlık Hizmetleri

18 How to do BI? The corporate World of Data XMLA Spreadsheets Application 1 Application 1 DB2 Özel Yazılım ve Danışmanlık Flat Hizmetleri DB1 Files info@kora.com.tr Application 1 Application 2 DB3

19 How to do BI? The corporate World of Data Needs change XMLA Spreadsheets Application 1 Application 1 DB2 Özel Yazılım ve Danışmanlık Flat Hizmetleri DB1 Files info@kora.com.tr Application 1 Application 2 DB3

20 How to do BI? Corporate BI Application feeds from integrated data environment to intel needs for all departments Application 1 Application 1 Özel Yazılım Integrated ve Danışmanlık Corporate Data Hizmetleri Environment (Data Warehouse & Data Marts) info@kora.com.tr Application 1 Application 2

21 Operational vs. Analytical Processing Operational processing: run day-to-day business for companies support business functionality by processing transactions accurately and efficiently Analytical (informational) processing: to support strategic and management decision making permits Özel users Yazılım to analyze ve Danışmanlık trends and patterns Hizmetleri with large amount of data over wide ranges of time

22 OLTP Systems OLTP System Characteristics Process real-time transactions of a business Contains data structures optimized for entries and edits Provides limited decision supportcapabilities OLTP Examples Order tracking Customer Özel services Yazılım ve Danışmanlık Hizmetleri Point-of-sales Service-based info@kora.com.tr sales Banking functions

23 Informational Systems Characteristics Provides data for business analysis processes Integrate data from heterogeneous source systems Combines validated source data Orginizes data into non-volatile, subject-specific groups Stores data in structures that are optimized for extraction and querying Özel Yazılım ve Danışmanlık Hizmetleri

24 Characteristic Operational Data Sources Data Content Current values Summarized and/or detail, archived Data Organization Application by application Subject areas across the enterprise Nature of Data Dynamic updates Static until refreshed Data Structure Suitable for updates Suitable for business analysis Usage Highly structured, repetitive Highly unstructured, heuristic/analytical # of Trans Özel Huge Yazılım ve Danışmanlık Low Hizmetleri to Medium Volume of Trans Small Medium to Huge info@kora.com.tr Informational Databases Time Periods Current period Historical, current, and future Queries Predictable/Planned Unpredictable/Adhoc/Unscheduled

25 Business Intelligence Market

26 More data than ever Özel Yazılım ve Danışmanlık Hizmetleri

27 Özel Yazılım ve Danışmanlık Hizmetleri

28 Özel Yazılım ve Danışmanlık Hizmetleri

29 Business Intelligence Tools & Users

30 BI Applications and Environment Data Query & Reporting Analytic Reporting OLAP Tool Mining Tool Consumers Application Application Tool Özel Yazılım Integrated ve Danışmanlık Corporate Data Hizmetleri Environment (Data Warehouse & Data Marts) Data Providers

31 Query & Reporting Tools Ad Hoc Query & Analysis Environment Oracle BI

32 Query & Reporting Tools Standard & Parameterized Reporting Dasboards Oracle BI

33 Multidimensional Analysis (OLAP) - Products Sold TIME Quarter 1 - Revenue MEASURES Jan Feb - Profit Quarter 2 Apr Mar May Jun Checking Saving Deposits Credit Checking PRODUCT Visa Credit Cards MC NY MA GA FL TX Northeast REGION South Essbase

34 Multidimensional Analysis (OLAP) Essbase

35 Data Mining: Extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databases. Data Data Preprocessing Data Attribute Business Selection and Transformation Mining Meaning Data Selected Transformed Patterns, Knowledge Warehouse Data Data Relationships Oracle Data Miner Cyrstal Ball

36 Data Mining Oracle Data Miner

37 BI Needs Data Consumers Queries... Queries... Queries... Queries... Queries Özel Yazılım Integrated ve Danışmanlık Corporate Data Hizmetleri Environment (Data Warehouse & Data Marts) Data Providers

38 The Usage Pyramid Data Mining Complex Ad-hoc OLAP Simple Ad-hoc Querying Standard & Parameterized Reporting

39 The User Spectrum Operator Farmer Explorer Miner Executive Tourist Embedded Data Mining Simple OLAP Standard Reports Advanced Simple Ad-hoc Analytics Parameterized Reports Complex Ad-hoc EIS, CPM Full OLAP Simple Use Complex Use

40 Operators Focused Use the intelligence derived by the Explorers and Farmers to improve business conditions Need fresh, detailed, day-to-day information Expect transactional performance and response times Demonstrate a fairly predictable pattern of usage See the world in terms of processes Predominantly use the ODS and sometimes OLAP datamarts Examples of operators Customer support represantatives (Manufacturing) Line managers (Inventory control) managers

41 Operator Needs Operator Needs Data mining Complex Ad-hoc OLAP Simple Ad-hoc Querying Standard & Parameterized Reporting

42 Farmers Clear Sighted Monitor the effect of decisions on the business by tracking kpm s Provide explorers with feedback on the effectiveness of their predictions Predictable patterns of usage: They know what data they want, how they want it displayed, when they want it and in what media See the world in dimensions and metrics Predominantly use OLAP datamarts and Paremeterized Reports Examples of farmers Sales analysts Financial analysts Market campaign managers Accounting analysts

43 Farmers Needs Farmers Needs Data mining Complex Ad-hoc OLAP Simple Ad-hoc Querying Standard & Parameterized Reporting

44 Explorers - innovative An out-of-the-box thinker Launches large and often unpredictable queries Often receives no results back Occaisonally receives incredible insight Strive to predict the future based on past results Are very knowledgeable about the content of data Demonstrate an unpredictable pattern of usage See the world in terms of data and data relationships May start with OLAP datamarts but often require thir own environment Examples of explorers Insurance actuaries Process control engineers Market research analysts

45 Explorers Needs Explorer Needs Data mining Complex Ad-hoc OLAP Simple Ad-hoc Querying Standard & Parameterized Reporting

46 Tourists Generalists Have a broad business perspective and are aware of the data produced by the business Use the Corporate Information Factory frequently Cover a breadth of material quickly but in little depth Are acccustomed to a consistent GUI Need the ability to search large banks of data without the a lot of typing Demonstrate unpredictable patterns of usage See the world in terms of business functions Predominantly use relational and OLAP datamarts Examples of tourists Executives Managers Casual users

47 Tourist Needs Tourist Needs Data mining Complex Ad-hoc OLAP Simple Ad-hoc Querying Standard & Parameterized Reporting

48 Miners Thorough Scan large amounts of detailed data looking for confirmation of a hypothesis or for a suspected pattern Have a good idea of what to expect prior to query execution Operate on a base of data thar has been preconditioned for analysis Demonstrate a reasonably predictable pattern of usage Interested in finding meaningful relationships in transactions Require their own mining environment Examples of miners Expert marketers Risk controllers Logistics specialists Statisticians

49 Miners Needs Miners Needs Data mining Complex Ad-hoc OLAP Simple Ad-hoc Querying Standard & Parameterized Reporting

50