Chapter 2 Data Governance and IT Architecture Support LongTerm Performance Prepared by Dr. Derek Sedlack, South University Learning Objectives Enterprise Architecture and Data Governance Information Management Cloud Services Add Agility Information Systems: The Basics Data Centers, Cloud Computing, and Virtualization Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management INFORMATION MANAGEMENT HARNESSES SCATTERED DATA Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management • Information Management – The use of IT tools and methods to collect, process, consolidate, store, and secure data from sources that are often fragmented and inconsistent. – Why a continuous plan is needed to guide, control, and govern IT growth. – Information management is critical to data security and compliance with continually evolving regulatory requirements, such as the Sarbanes-Oxley Act, Basel III, the Computer Fraud and Abuse Act (CFAA), the USA PATRIOT Act, and the Health Insurance Portability and Accountability Act (HIPAA). Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management • Data Silos – Stand alone data stores not accessible by other information systems that need data, cannon consistently be updated. – Exist from a lack of IT architecture, only support single functions, and do not support crossfunctional needs. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management • Key Performance Indicators (KPIs) – These measures demonstrate the effectiveness of a business process at achieving organizational goals. – Present data in easy-to-comprehend and comparison-ready formats. KPI examples: current ratio; accounts payable turnover; net profit margin; new followers per week; cost per lead; order status. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management Figure 2.4 Data (or information) silos are ISs that do not have the capability to exchange data with other ISs, making timely coordination and communication across functions or departments difficult. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management • Reasons information deficiencies are still a problem – Data Silos – Lost of bypassed data – Poorly designed interfaces – Nonstandardized data formats – Cannot hit moving targets Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management Global, mobile workforce 62% of the workforce works outside an office at some point. This number is increasing. Mobility-driven consumerization Growing number of cloud collaboration services. Principle of “any” Growing need to connect anybody, anytime, anywhere on any device Figure 2.5 Factors that are increasing demand for collaboration technology. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management • Obvious benefits of information management – Improves decision quality – Improves the accuracy and reliability of management predictions – Reduces the risk of noncompliance – Reduces time and cost Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Management 1. Explain information management. 2. Why do organizations still have information deficiency problems? 3. What is a data silo? 4. Explain KPIs and give an example. 5. What three factors are driving collaboration and information sharing? 6. What are the business benefits of information management? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Enterprise Architecture and Data Governance Information Management Cloud Services Add Agility Information Systems: The Basics Data Centers, Cloud Computing, and Virtualization Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance • Enterprise architecture (EA) – The way IT systems and processes are structured. – Helps or impedes day-to-day operations and efforts to execute business strategy. – Solves two critical challenges: where are we going; how do we get there? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance • Strategic Focus – IT systems’ complexity – Poor business alignment • Business and IT Benefits of EA – Cuts IT costs; increases productivity with information, insight, and ideas – Determines competitiveness, flexibility, and IT economics – Aligns IT capabilities with business strategy to grow, innovate, and respond to market demands – Reduces risk of buying or building systems and enterprise apps Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance Business Architecture Application Architecture Data Architecture Technical Architecture Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance • Enterprise-wide Data Governance – Crosses boundaries and used by people through the enterprise. – Increased importance through new regulations and pressure to reduce costs. – Reduces legal risks associated with unmanaged or inconsistently managed information Dependent on Governance Food Industry Financial Services Industry Healthcare Industry Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance • Master Data & Management (MDM) – Creates high-quality trustworthy data: • Running the business with transactional or operational use • Improving the business with analytic use – Requires strong data governance to manage availability, usability, integrity, and security. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance • Politics: The People Conflict – Cultures of distrust between technology and employees may exist. – Genuine commitment to change can bridge the divide with support from the senior management. – Methodologies can only provide a framework, not solve people problems Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Enterprise Architecture and Data Governance 1. Explain the relationship between complexity and planning. Give an example. 2. Explain enterprise architecture. 3. What are the four components of EA? 4. What are the business benefits of EA? 5. How can EA maintain alignment between IT and business strategy? 6. What are the two ways that data are used in an organization? 7. What is the function of data governance? 8. Why has interest in data governance and MDM increased? 9. What role does personal conflict or politics play in the success of data governance? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Enterprise Architecture and Data Governance Information Management Cloud Services Add Agility Information Systems: The Basics Data Centers, Cloud Computing, and Virtualization Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics • DATA, INFORMATION, & KNOWLEDGE – Raw data describes products, customers, events, activities, and transactions that are recorded, classified, and stored. – Information is processed, organized, or put into context data with meaning and value to the recipient. – Knowledge is conveyed information as applied to a current problem or activity. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics • DATA, INFORMATION, & KNOWLEDGE – Raw data describes products, customers, events, activities, and transactions that are recorded, classified, and stored. Data Information Knowledge Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics Figure 2.8 Input-processing-output model. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics • Transaction Processing Systems (TPS) – Internal transactions: originate or occur within the organization (payroll, purchases, etc.). – External transactions: originate outside the organization (customers, suppliers, etc.). – Improve sales, customer satisfaction, and reduce many other types of data errors with financial impacts. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics • Batch v. Online Real-Time Processing – Batch Processing: collects all transactions for a time period, then processes the data and updates the data store. – OLTP: processes each transaction as it occurs (realtime). – Batch processing costs less than OLTP, but may be inaccurate from update delays. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics • Management Information Systems (MIS) – General-purpose reporting systems that provide reports to managers for tracking operations, monitoring, and control. Periodic: reports created or run according to a pre-set schedule. Exception: generated only when something is outside designated parameters. Ad Hoc, or On Demand: unplanned, generated as needed. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics • Decision Support Systems (DSS) – Interactive applications that support decision making. – Support unstructured and semi-structured decisions with the following characteristics: 1. Easy-to-use interactive interface 2. Models or formulas that enable sensitivity analysis 3. Data from multiple sources Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Information Systems: The Basics • Transaction Issues – Huge database transactions causes volatility – constant use or updates. – Makes databases impossible for complex decision making and problem-solving tasks. Data is loaded to a data warehouse where ETL (extract, transform, and load) is better for analysis. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Business Process Management and Improvement 1. 2. 3. 4. 5. Contrast data, information, and knowledge. Define TPS and give an example. When is batch processing used? When are real-time processing capabilities needed? Explain why TPSs need to process incoming data before they are stored. 6. Define MIS and DSS and give an example of each. 7. Why are databases inappropriate for doing data analysis? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Enterprise Architecture and Data Governance Information Management Cloud Services Add Agility Information Systems: The Basics Data Centers, Cloud Computing, and Virtualization Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • IT Infrastructures – On-premises data centers – Virtualization – Cloud Computing Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Data Centers – Large numbers of network servers used for the storage, processing, management, distribution, and archiving of data, systems, Web traffic, services, and enterprise applications. National Climatic Data Center U.S. National Security Agency Apple Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Business is Reliant Upon data – Uber (car-hailing service) • Users flooded social media with complaints. – WhatsApp (smartphone text-messaging service) • Competition added 2 million new registered users within 24 hours of WhatsApp outage (a record). Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Unified Data Center – Cisco’s single solution integrating computing, storage, networking, virtualization, and management into a single (unified) platform. – Virtualization gives greater IT flexibility and cutting costs: • Instant access to data any time in any format • Respond faster to changing data analytic needs • Cut complexity and cost Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization Unified Data Center compared to traditional data integration and replication methods: Greater Agility Streamlined Approach Better Insight Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • What is “The Cloud”? – A general term for infrastructure that uses the Internet and private networks to access, share, and deliver computing resources. – Scalable delivery as a service to end-users over a network. – Should be approached with greater diligence than other IT decisions as a new technology including Vendor Management and ServiceLevel Agreements. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Service-Level Agreements – A negotiated agreement between a company and service provider that can be a legally binding contract or an informal contract. – The goal is not building the best SLA terms, but getting the terms that are most meaningful to the business. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Types of Clouds – Private Cloud: Single-tenant environments with stronger security and control (retained) for regulated industries and critical data. – Public Cloud: Multiple-tenant virtualized services utilizing the same pool of servers across a public network (distributed). Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Cloud Infrastructure – Provided on demand for storage virtualization, network virtualization, and hardware virtualization. Software or virtualization layer creates virtual machines (VMs) where the CPU, RAM, HD, NIC, and other components behave as hardware, but are created with software. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Virtualization – Created by a software layer (virtualization layer) containing its own operating system and applications as a physical computer. Software As a Service Platform As a Service Infrastructure As a Service Figure 2.17 Virtual machines running on a simple computer hardware layer. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization • Characteristics & Benefits – Memory-intensive • Huge amounts of RAM due to massive processing requirements – Energy-efficient • Up to 95% reduction in energy use per server through less physical hardware – Scalability and load balancing • Handles dynamic demand requests like during the Super Bowl or World Series Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Data Centers, Cloud Computing, and Virtualization 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. What is a data center? Describe cloud computing. What is the difference between data centers and cloud computing? What are the benefits of cloud computing? How can cloud computing solve the problems of managing software licenses? What is an SLA? Why are SLAs important? What factors should be considered when selecting a cloud vendor or provider? When are private clouds used instead of public clouds? Explain three issues that need to be addressed when moving to cloud computing or services. How does a virtual machine (VM) function? Explain virtualization. What are the characteristics and benefits of virtualization? When is load balancing important? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Enterprise Architecture and Data Governance Information Management Cloud Services Add Agility Information Systems: The Basics Data Centers, Cloud Computing, and Virtualization Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Cloud Services Add Agility • Software as a Service (SaaS) – End-user apps, like SalesForce • Platform as a Service (PaaS) – Tools and services making coding and deployment faster and more efficient, like Google App Engine • Infrastructure as a Service (IaaS) – Hardware and software that power computing resources, like EC2 & S3 (Amazon Web Services) • Data as a Service (DaaS) – Data shared among clouds, systems, apps, regardless the data source or storage location. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Cloud Services Add Agility • Data as a Service (DaaS) – Easier for data architects to select data from different pools, filter out sensitive data, and make the remaining data available on-demand. – Eliminates risks and burdens of data management to a third-party cloud provider. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Cloud Services Add Agility • Cloudy Weather Ahead? – Various at-a-service models (such as CRM and HR management) are still responsible for regulatory compliance. – Legal departments become involved due to high stakes around legal and compliance issues. – Cut costs, flexibility, and improved responsiveness require IT, legal, and senior management oversight. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 2 Cloud Services Add Agility 1. 2. 3. 4. 5. 6. What is SaaS? Describe the cloud computing stack. What is PaaS? What is IaaS? Why is DaaS growing in popularity? How might companies risk violating regulation or compliance requirements with cloud services? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Management, Big Data Analytics, and Records Management Prepared by Dr. Derek Sedlack, South University Learning Objectives Data Warehouse and Big Data Analytics Database Management Systems Electronic Records Management Data and Text Mining Business Intelligence Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Databases – Collections of data sets or records stored in a systematic way. – Stores data generated by business apps, sensors, operations, and transaction-processing systems (TPS). – The data in databases are extremely volatile. – Medium and large enterprises typically have many databases of various types. Volatile data changes frequently Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Data Warehouses – Integrate data from multiple databases and data silos, and organize them for complex analysis, knowledge discovery, and to support decision making. – May require formatting processing and/or standardization. – Loaded at specific times making them non-volatile and ready for analysis. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Data Marts – Small-scale data warehouses that support a single function or one department. – Enterprises that cannot afford to invest in data warehousing may start with one or more data marts. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Business intelligence (BI) – Tools and techniques that process data and conduct statistical analysis for insight and discovery. – Used to discover meaningful relationships in the data, keep informed of real time, detect trends, and identify opportunities and risks. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Database Management System (DBMS) – Integrate with data collection systems such as TPS and business applications. – Stores data in an organized way. – Provides facilities for accessing and managing data. – Standard database model adopted by most enterprises. – Store data in tables consisting of columns and rows, similar to the format of a spreadsheet. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Relational Management System (DBMS) – Provides access to data using a declarative language. • Declarative Language – Simplifies data access by requiring that users only specify what data they want to access without defining how they will be achieved. – Structured Query Language (SQL) is an example of a declarative language: SELECT column_name(s) FROM table_name WHERE condition Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • DBMS Functions – Data filtering and profiling – Data integrity and maintenance – Data synchronization – Data security – Data access Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems Online Transaction Processing and Online Analytics Processing • Online Transaction Processing (OLTP) – Designed to manage transaction data, which are volatile & break down complex information into simpler data tables to strike a balance between transaction-processing efficiency and query efficiency. – Cannot be optimized for data mining • Online Analytics Processing (OLAP) – A means of organizing large business databases. – Divided into one or more cubes that fit the way business is conducted. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • DBMSs (mid-2014) – Oracle’s MySQL – Microsoft’s SQL Server – PostgreSQL – IBM’s DB2 – Teradata Database. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Trend Toward NoSQL Systems – Higher performance – Easy distribution of data on different nodes • enables scalability and fault tolerance – Greater flexibility – Simpler administration Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems Centralized and Distributed Database Architecture • Centralized Database Architecture – Better control of data quality. – Better IT security. • Distributed Database Architecture – Allow both local and remote access. – Use client/server architecture to process requests. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems Garbage In, Garbage Out • Dirty Data – Lacks integrity/validation and reduces user trust. – Incomplete, out of context, outdated, inaccurate, inaccessible, or overwhelming. Cost of Poor Quality Data Lost Business Cost to Prevent Errors Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Cost to Correct Errors Chapter 3 Database Management Systems • Principle of Diminishing Data Value – The value of data diminishes as they age. – Blind spots (lack of data availability) of 30 days or longer inhibit peak performance. – Global financial services institutions rely on nearreal-time data for peak performance. • Principle of 90/90 Data Use – As high as 90 percent, is seldom accessed after 90 days (except for auditing purposes). – Roughly 90 percent of data lose most of their value after 3 months. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems • Principle of data in context – The capability to capture, process, format, and distribute data in near real time or faster requires a huge investment in data architecture. – The investment can be justified on the principle that data must be integrated, processed, analyzed, and formatted into “actionable information.” Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems Data Life Cycle Figure 3.11 Data life cycle. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems Figure 3.12 An enterprise has transactional, master, and analytical data. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Database Management Systems 1. Describe a database and a database management system (DBMS). 2. Explain what an online transaction-processing (OLAP) system does. 3. Why are data in databases volatile? 4. Explain what processes DBMSs are optimized to perform. 5. What are the business costs or risks of poor data quality? 6. Describe the data life cycle. 7. What is the function of master data management (MDM)? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Data Warehouse and Big Data Analytics Database Management Systems Electronic Records Management Data and Text Mining Business Intelligence Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Market share – Percentage of total sales in a market captured by a brand, product, or company. • Operating Margin – A measure of the percent of a company’s revenue left over after paying variable costs: wages, raw materials, etc. – Increased margins mean earning more per dollar of sales. – The higher the operating margin, the better. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics TORTURE DATA LONG ENOUGH AND IT WILL CONFESS . . . BUT MAY NOT TELL THE TRUTH Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Human Expertise and Judgment Required – Data are worthless if you cannot analyze, interpret, understand, and apply the results in context. – Data need to be prepared for analysis. – Dirty data degrade the value of analytics. – Data must be put into meaningful context. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Enterprise data warehouses (EDW) – Data warehouses that pull together data from disparate sources and databases across an entire. – Warehouses are the primary source of cleansed data for analysis, reporting, and Business Intelligence (BI). – Their high costs can be subsidized by using Data marts. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Procedures to Prepare EDW Data for Analytics – Extract from designated databases. – Transform by standardizing formats, cleaning the data, integration. – Loading into a data warehouse. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Active Data Warehouse (ADW) – Real-time data warehousing and analytics. – Transform by standardizing formats, cleaning the data, integration. • They Provide – Interaction with a customer to provide superior customer service. – Respond to business events in near real time. – Share up-to-date status data among merchants, vendors, customers, and associates. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Supporting Actions as well as Decisions – Marketing and Sales – Pricing and Contracts – Forecasting – Sales – Financial Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Really Big Data – Low-cost sensors collect data in real time in all types of physical things (machine-generated sensor data): • Regulate temperature and climate • Detect air particles for contamination • Machinery conditions/failures • Engine wear/maintenance Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics Figure 3.16 Machine generated data from physical objects are becoming a much larger portion of big data and analytics.. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics • Hadoop and MapReduce – Hadoop is an Apache processing platform that places no conditions on the processed data structure. – MapReduce provides a reliable, fault-tolerant software framework to write applications easily that process vast amounts of data (multi-terabyte datasets) in-parallel on large clusters (thousands of nodes) of commodity hardware. • Map stage: breaks up huge data into subsets • Reduce stage: recombines partial results Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data Warehouse and Big Data Analytics 1. Why are human expertise and judgment important to data analytics? Give an example. 2. What is the relationship between data quality and the value of analytics? 3. Why do data need to be put into a meaningful context? 4. What are the differences between databases and data warehouses? 5. Explain ETL and CDC. 6. What is an advantage of an active data warehouse (ADW)? 7. Why might a company invest in a data mart? 8. How can manufacturers and health care benefit from data analytics? 9. Explain how Hadoop implements MapReduce in two stages. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Data Warehouse and Big Data Analytics Database Management Systems Electronic Records Management Data and Text Mining Business Intelligence Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data and Text Mining • Creating Business Value – Business Analytics: the entire function of applying technologies, algorithms, human expertise, and judgment. – Data Mining: software that enables users to analyze data from various dimensions or angles, categorize them, and find correlative patterns among fields in the data warehouse. – Text Mining: broad category involving interpreted words and concepts in context. – Sentimental Analysis: trying to understand consumer intent. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data and Text Mining • Text Analytics (Mining) Procedure – Exploration • Simple word counts • Topics consolidation – Preprocessing • Standardization • May be 80% of processing time • Grammar and spell checking – Categorizing and Modelling • Create business rules and train models for accuracy and precision Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data and Text Mining • Text Analytics Procedure – Exploration • Simple word counts • Topics consolidation – Preprocessing • Standardization • May be 80% of processing time • Grammar and spell checking – Categorizing and Modelling • Create business rules and train models for accuracy and precision Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Data and Text Mining 1. Describe data mining. 2. How does data mining generate or provide value? Give an example. 3. What is text mining? 4. Explain the text mining procedure. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Data Warehouse and Big Data Analytics Database Management Systems Electronic Records Management Data and Text Mining Business Intelligence Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Business Intelligence • Key to competitive advantage – Across industries in all size enterprises – Used in operational management, business process, and decision making – Provides moment of value to decision makers – Unites data, technology, analytics, & human knowledge to optimize decisions Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Business Intelligence • Challenges – Data Selection & Quality – Alignment with Business Strategy and BI Strategy • Alignment – Clearly articulates business strategy – Deconstructs business strategy into targets – Identifies PKIs – Prioritizes PKIs – Creates a plan based on priorities – Transform based on strategic results and changes Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Business Intelligence Smart Devices Everywhere have created demand for effortless 24/7 access to insights. Advanced BI and Analytics help to ask questions that were previously unknown and unanswerable. Data is Big Business when they provide insight that supports decisions and action. Cloud Enabled BI and Analytics are providing low-cost and flexible solutions. Figure 3.20 Four factors contributing to increased use of BI. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Business Intelligence • BI Architecture and Analytics – Advances in response to big data and end-user performance demands. – Hosted on public or private clouds. – Limits IT staff and controls costs – May slow response time, add security and backup risks Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Business Intelligence 1. How has BI improved performance management at Quicken Loans? 2. What are the business benefits of BI? 3. What are two data-related challenges that must be resolved for BI to produce meaningful insight? 4. What are the steps in a BI governance program? 5. What is a business-driven development approach? 6. What does it mean to drill down, and why is it important? 7. What four factors are contributing to increased use of BI? 8. How did BI help CarMax achieve record-setting revenue growth? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Learning Objectives Data Warehouse and Big Data Analytics Database Management Systems Electronic Records Management Data and Text Mining Business Intelligence Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Electronic Records Management • Business Records – Documentation of a business event, action, decision, or transaction. • Electronic Records Management (EMR) – Workflow software, authoring tools, scanners, and databases that manage and archive electronic documents and image paper documents. – Index and store documents according to company policy or legal compliance. – Success depends on partnership of key players. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Electronic Records Management • Best Practices – Effective systems capture all business data. – Input from online forms, bar codes, sensors, websites, social sites, copiers, e-mails, and more. • Industry Standards – Association for Information and Image Management (AIIM; www.aiim.org) – National Archives and Records Administration (NARA; www.archives.gov) – ARMA International (formerly the Association of Records Managers and Administrators; www.arma.org) Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Electronic Records Management • Primary Benefits – Access and use the content contained in documents. – Cut labor costs by automating business processes. – Reduce time and effort to locate required information for decision making. – Improve content security, thereby reducing intellectual property theft risks. – Minimizes content printing, storing, and searching costs. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Electronic Records Management • DISASTER RECOVERY, BUSINESS CONTINUITY, AND COMPLIANCE 1. Does the software meet the organization’s needs? For example, can the DMS be installed on the existing network? Can it be purchased as a service? 2. Is the software easy to use and accessible from Web browsers, office applications, and e-mail applications? If not, people will not use it. 3. Does the software have lightweight, modern Web and graphical user interfaces that effectively support remote users? 4. Before selecting a vendor, it is important to examine workflows and how data, documents, and communications flow throughout the company. Copyright © 2015 John Wiley & Sons, Inc. All rights reserved. Chapter 3 Electronic Records Management 1. What are business records? 2. Why is ERM a strategic issue rather than simply an IT issue? 3. Why might a company have a legal duty to retain records? Give an example. 4. Why is creating backups an insufficient way to manage an organization’s documents? 5. What are the benefits of ERM? Copyright © 2015 John Wiley & Sons, Inc. All rights reserved.
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