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Agile Data Warehousing for the Enterprise

Agile Data Warehousing for the Enterprise
A Guide for Solution Architects and Project Leaders

by Ralph Hughes

  • Publisher : Newnes
  • Release : 2015-09-19
  • Pages : 562
  • ISBN : 0123965187
  • Language : En, Es, Fr & De
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Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked. Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs. Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines. Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way. Learn how to quickly define scope and architecture before programming starts Includes techniques of process and data engineering that enable iterative and incremental delivery Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges Use the provided 120-day road map to establish a robust, agile data warehousing program

Agile Data Warehousing Project Management

Agile Data Warehousing Project Management
Business Intelligence Systems Using Scrum

by Ralph Hughes

  • Publisher : Newnes
  • Release : 2013
  • Pages : 356
  • ISBN : 0123964636
  • Language : En, Es, Fr & De
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What is agile data warehousing? -- Iterative development in a nutshell -- Streamlining project management -- Authoring better user stories -- Deriving initial project backlogs -- Developer stories for data integration -- Estimating and segmenting projects -- Adapting agile for data warehousing -- Starting and scaling agile data warehousing.

Agile Data Warehousing for the Enterprise

Agile Data Warehousing for the Enterprise
A Book

by Ralph Hughes

  • Publisher : Unknown Publisher
  • Release : 2015
  • Pages : 562
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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Building upon his earlier book that detailed agile data warehousing programming techniques for the Scrum master, Ralph's latest work illustrates the agile interpretations of the remaining software engineering disciplines: Requirements management benefits from streamlined templates that not only define projects quickly, but ensure nothing essential is overlooked. Data engineering receives two new "hyper modeling" techniques, yielding data warehouses that can be easily adapted when requirements change without having to invest in ruinously expensive data-conversion programs. Quality assurance advances with not only a stereoscopic top-down and bottom-up planning method, but also the incorporation of the latest in automated test engines. Use this step-by-step guide to deepen your own application development skills through self-study, show your teammates the world's fastest and most reliable techniques for creating business intelligence systems, or ensure that the IT department working for you is building your next decision support system the right way. Learn how to quickly define scope and architecture before programming starts Includes techniques of process and data engineering that enable iterative and incremental delivery Demonstrates how to plan and execute quality assurance plans and includes a guide to continuous integration and automated regression testing Presents program management strategies for coordinating multiple agile data mart projects so that over time an enterprise data warehouse emerges Use the provided 120-day road map to establish a robust, agile data warehousing program.

Modeling the Agile Data Warehouse with Data Vault

Modeling the Agile Data Warehouse with Data Vault
A Book

by Hans Hultgren

  • Publisher : Unknown Publisher
  • Release : 2012-11-16
  • Pages : 434
  • ISBN : 9780615723082
  • Language : En, Es, Fr & De
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Data Modeling for Agile Data Warehouse using Data Vault Modeling Approach. Includes Enterprise Data Warehouse Architecture. This is a complete guide to the data vault data modeling approach. The book also includes business and program considerations for the agile data warehousing and business intelligence program. There are over 200 diagrams and figures concerning modeling, core business concepts, architecture, business alignment, semantics, and modeling comparisons with 3NF and Dimensional modeling.

Extreme Scoping

Extreme Scoping
An Agile Approach to Enterprise Data Warehousing and Business Intelligence

by Larissa Moss

  • Publisher : Technics Publications Llc
  • Release : 2013-08-15
  • Pages : 308
  • ISBN : 9781935504535
  • Language : En, Es, Fr & De
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Extreme Scoping, based on the Business Intelligence Roadmap, will show you how to build analytics applications rapidly yet not sacrifice data management and enterprise architecture.

Extreme Scoping

Extreme Scoping
An Agile Approach to Enterprise Data Warehousing and Business Intelligence

by Larissa T. Moss

  • Publisher : Technics Publications
  • Release : 2013-09-01
  • Pages : 306
  • ISBN : 1634620240
  • Language : En, Es, Fr & De
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Do your business intelligence (BI) projects take too long to deliver? Is the value of the deliverables less than satisfactory? Do these projects propagate poor data management practices? If you screamed “yes” to any of these questions, read this book to master a proven approach to building your enterprise data warehouse and BI initiatives. Extreme Scoping, based on the Business Intelligence Roadmap, will show you how to build analytics applications rapidly yet not sacrifice data management and enterprise architecture. In addition, all of the roles required to deliver all seven steps of this agile methodology are explained along with many real-world examples. From Wayne Eckerson’s Foreword I’ve read many books about data warehousing and business intelligence (BI). This book by Larissa Moss is one of the best. I should not be surprised. Larissa has spent years refining the craft of designing, building, and delivering BI applications. Over the years, she has developed a keen insight about what works and doesn’t work in BI. This book brings to light the wealth of that development experience. Best of all, this is not some dry text that laboriously steps readers through a technical methodology. Larissa expresses her ideas in a clear, concise, and persuasive manner. I highlighted so many beautifully written and insightful paragraphs in her manuscript that it became comical. I desperately wanted the final, published book rather than the manuscript so I could dog-ear it to death and place it front-and-center in my office bookshelf! From David Well’s Foreword Extreme Scoping is rich with advice and guidance for virtually every aspect of BI projects from planning and requirements to deployment and from back-end data management to front-end information and analytics services. Larissa is both a pragmatist and an independent thinker. Those qualities come through in the style of this book. Extreme Scoping is a well-written book that is easy to absorb. It is not full of surprises. It is filled with a lot of common sense and lessons learned through experience.

Agile Analytics

Agile Analytics
A Value-driven Approach to Business Intelligence and Data Warehousing

by Ken Collier

  • Publisher : Addison-Wesley
  • Release : 2012
  • Pages : 329
  • ISBN : 032150481X
  • Language : En, Es, Fr & De
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Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. However, conventional Agile methods must be carefully adapted to address the unique characteristics of DW/BI projects. In Agile Analytics, Agile pioneer Ken Collier shows how to do just that. Collier introduces platform-agnostic Agile solutions for integrating infrastructures consisting of diverse operational, legacy, and specialty systems that mix commercial and custom code. Using working examples, he shows how to manage analytics development teams with widely diverse skill sets and how to support enormous and fast-growing data volumes. Collier's techniques offer optimal value whether your projects involve "back-end" data management, "front-end" business analysis, or both. Part I focuses on Agile project management techniques and delivery team coordination, introducing core practices that shape the way your Agile DW/BI project community can collaborate toward success Part II presents technical methods for enabling continuous delivery of business value at production-quality levels, including evolving superior designs; test-driven DW development; version control; and project automation Collier brings together proven solutions you can apply right now--whether you're an IT decision-maker, data warehouse professional, database administrator, business intelligence specialist, or database developer. With his help, you can mitigate project risk, improve business alignment, achieve better results--and have fun along the way.

An Introduction to Agile Data Engineering Using Data Vault 2. 0

An Introduction to Agile Data Engineering Using Data Vault 2. 0
Better Data Modeling

by Kent Graziano

  • Publisher : Unknown Publisher
  • Release : 2015-11-22
  • Pages : 50
  • ISBN : 9781796584936
  • Language : En, Es, Fr & De
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The world of data warehousing is changing. Big Data & Agile are hot topics. But companies still need to collect, report, and analyze their data. Usually this requires some form of data warehousing or business intelligence system. So how do we do that in the modern IT landscape in a way that allows us to be agile and either deal directly or indirectly with unstructured and semi structured data?The Data Vault System of Business Intelligence provides a method and approach to modeling your enterprise data warehouse (EDW) that is agile, flexible, and scalable. This book will give you a short introduction to Agile Data Engineering for Data Warehousing and Data Vault 2.0. I will explain why you should be trying to become Agile, some of the history and rationale for Data Vault 2.0, and then show you the basics for how to build a data warehouse model using the Data Vault 2.0 standards.In addition, I will cover some details about the Business Data Vault (what it is) and then how to build a virtual Information Mart off your Data Vault and Business Vault using the Data Vault 2.0 architecture.So if you want to start learning about Agile Data Engineering with Data Vault 2.0, this book is for you.

Agile Data Warehousing Project Management

Agile Data Warehousing Project Management
Business Intelligence Systems Using Scrum

by Ralph Hughes

  • Publisher : Newnes
  • Release : 2012-12-28
  • Pages : 366
  • ISBN : 0123965179
  • Language : En, Es, Fr & De
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You have to make sense of enormous amounts of data, and while the notion of “agile data warehousing might sound tricky, it can yield as much as a 3-to-1 speed advantage while cutting project costs in half. Bring this highly effective technique to your organization with the wisdom of agile data warehousing expert Ralph Hughes. Agile Data Warehousing Project Management will give you a thorough introduction to the method as you would practice it in the project room to build a serious “data mart. Regardless of where you are today, this step-by-step implementation guide will prepare you to join or even lead a team in visualizing, building, and validating a single component to an enterprise data warehouse. Provides a thorough grounding on the mechanics of Scrum as well as practical advice on keeping your team on track Includes strategies for getting accurate and actionable requirements from a team’s business partner Revolutionary estimating techniques that make forecasting labor far more understandable and accurate Demonstrates a blends of Agile methods to simplify team management and synchronize inputs across IT specialties Enables you and your teams to start simple and progress steadily to world-class performance levels

Data Warehousing Fundamentals for IT Professionals

Data Warehousing Fundamentals for IT Professionals
A Book

by Paulraj Ponniah

  • Publisher : John Wiley & Sons
  • Release : 2011-09-20
  • Pages : 608
  • ISBN : 1118211308
  • Language : En, Es, Fr & De
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CUTTING-EDGE CONTENT AND GUIDANCE FROM A DATA WAREHOUSING EXPERT—NOW EXPANDED TO REFLECT FIELD TRENDS Data warehousing has revolutionized the way businesses in a wide variety of industries perform analysis and make strategic decisions. Since the first edition of Data Warehousing Fundamentals, numerous enterprises have implemented data warehouse systems and reaped enormous benefits. Many more are in the process of doing so. Now, this new, revised edition covers the essential fundamentals of data warehousing and business intelligence as well as significant recent trends in the field. The author provides an enhanced, comprehensive overview of data warehousing together with in-depth explanations of critical issues in planning, design, deployment, and ongoing maintenance. IT professionals eager to get into the field will gain a clear understanding of techniques for data extraction from source systems, data cleansing, data transformations, data warehouse architecture and infrastructure, and the various methods for information delivery. This practical Second Edition highlights the areas of data warehousing and business intelligence where high-impact technological progress has been made. Discussions on developments include data marts, real-time information delivery, data visualization, requirements gathering methods, multi-tier architecture, OLAP applications, Web clickstream analysis, data warehouse appliances, and data mining techniques. The book also contains review questions and exercises for each chapter, appropriate for self-study or classroom work, industry examples of real-world situations, and several appendices with valuable information. Specifically written for professionals responsible for designing, implementing, or maintaining data warehousing systems, Data Warehousing Fundamentals presents agile, thorough, and systematic development principles for the IT professional and anyone working or researching in information management.

Building a Scalable Data Warehouse with Data Vault 2.0

Building a Scalable Data Warehouse with Data Vault 2.0
A Book

by Dan Linstedt,Michael Olschimke

  • Publisher : Morgan Kaufmann
  • Release : 2015-09-15
  • Pages : 684
  • ISBN : 0128026480
  • Language : En, Es, Fr & De
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The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. "Building a Scalable Data Warehouse" covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. Important data warehouse technologies and practices. Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse Demystifies data vault modeling with beginning, intermediate, and advanced techniques Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0

Agile Data Warehousing

Agile Data Warehousing
Delivering World-class Business Intelligence Systems Using Scrum and XP

by Ralph Hughes

  • Publisher : iUniverse
  • Release : 2008
  • Pages : 324
  • ISBN : 0595471676
  • Language : En, Es, Fr & De
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Contains a six-stage plan for starting new warehouse projects and guiding programmers step-by-step until they become a world-class, Agile development team. It describes also how to avoid or contain the fierce opposition that radically new methods can encounter from the traditionally-minded IS departments found in many large companies.

Agile Data Warehouse Design

Agile Data Warehouse Design
Collaborative Dimensional Modeling, from Whiteboard to Star Schema

by Lawrence Corr,Jim Stagnitto

  • Publisher : DecisionOne Consulting
  • Release : 2011-11
  • Pages : 304
  • ISBN : 0956817203
  • Language : En, Es, Fr & De
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Agile Data Warehouse Design is a step-by-step guide for capturing data warehousing/business intelligence (DW/BI) requirements and turning them into high performance dimensional models in the most direct way: by modelstorming (data modeling ] brainstorming) with BI stakeholders. This book describes BEAM, an agile approach to dimensional modeling, for improving communication between data warehouse designers, BI stakeholders and the whole DW/BI development team. BEAM provides tools and techniques that will encourage DW/BI designers and developers to move away from their keyboards and entity relationship based tools and model interactively with their colleagues. The result is everyone thinks dimensionally from the outset! Developers understand how to efficiently implement dimensional modeling solutions. Business stakeholders feel ownership of the data warehouse they have created, and can already imagine how they will use it to answer their business questions. Within this book, you will learn: Agile dimensional modeling using Business Event Analysis & Modeling (BEAM ) Modelstorming: data modeling that is quicker, more inclusive, more productive, and frankly more fun! Telling dimensional data stories using the 7Ws (who, what, when, where, how many, why and how) Modeling by example not abstraction; using data story themes, not crow's feet, to describe detail Storyboarding the data warehouse to discover conformed dimensions and plan iterative development Visual modeling: sketching timelines, charts and grids to model complex process measurement - simply Agile design documentation: enhancing star schemas with BEAM dimensional shorthand notation Solving difficult DW/BI performance and usability problems with proven dimensional design patterns LawrenceCorr is a data warehouse designer and educator. As Principal of DecisionOne Consulting, he helps clients to review and simplify their data warehouse designs, and advises vendors on visual data modeling techniques. He regularly teaches agile dimensional modeling courses worldwide and has taught dimensional DW/BI skills to thousands of students. Jim Stagnitto is a data warehouse and master data management architect specializing in the healthcare, financial services, and information service industries. He is the founder of the data warehousing and data mining consulting firm Llumino.

The Data Warehouse Mentor: Practical Data Warehouse and Business Intelligence Insights

The Data Warehouse Mentor: Practical Data Warehouse and Business Intelligence Insights
A Book

by Robert Laberge

  • Publisher : McGraw Hill Professional
  • Release : 2011-05-12
  • Pages : 416
  • ISBN : 0071745327
  • Language : En, Es, Fr & De
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Develop a custom, agile data warehousing and business intelligence architecture Empower your users and drive better decision making across your enterprise with detailed instructions and best practices from an expert developer and trainer. The Data Warehouse Mentor: Practical Data Warehouse and Business Intelligence Insights shows how to plan, design, construct, and administer an integrated end-to-end DW/BI solution. Learn how to choose appropriate components, build an enterprise data model, configure data marts and data warehouses, establish data flow, and mitigate risk. Change management, data governance, and security are also covered in this comprehensive guide. Understand the components of BI and data warehouse systems Establish project goals and implement an effective deployment plan Build accurate logical and physical enterprise data models Gain insight into your company's transactions with data mining Input, cleanse, and normalize data using ETL (Extract, Transform, and Load) techniques Use structured input files to define data requirements Employ top-down, bottom-up, and hybrid design methodologies Handle security and optimize performance using data governance tools Robert Laberge is the founder of several Internet ventures and a principle consultant for the IBM Industry Models and Assets Lab, which has a focus on data warehousing and business intelligence solutions.

The Sentient Enterprise

The Sentient Enterprise
The Evolution of Business Decision Making

by Oliver Ratzesberger,Mohanbir Sawhney

  • Publisher : John Wiley & Sons
  • Release : 2017-09-18
  • Pages : 176
  • ISBN : 1119438799
  • Language : En, Es, Fr & De
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Mohan and Oliver have been very fortunate to have intimate views into the data challenges that face the largest organizations and institutions across every possible industry—and what they have been hearing about for some time is how the business needs to use data and analytics to their advantage. They continually hear the same issues, such as: We're spending valuable meeting time wondering why everyone's data doesn't match up. We can't leverage our economies of scale while remaining agile with data. We need self-serve apps that let the enterprise experiment with data and accelerate the development process. We need to get on a more predictive curve to ensure long-term success. To really address the data concerns of today's enterprise, they wanted to find a way to help enterprises achieve the success they seek. Not as a prescriptive process—but a methodology to become agile and leverage data and analytics to drive a competitive advantage. You know, it's amazing what can happen when two people with very different perspectives get together to solve a big problem. This evolutionary guide resulted from the a-ha moment between these two influencers at the top of their fields—one, an academic researcher and consultant, and the other, a longtime analytics practitioner and chief product officer at Teradata. Together, they created a powerful framework every type of business can use to connect analytic power, business practices, and human dynamics in ways that can transform what is currently possible.

Data Warehouse Requirements Engineering

Data Warehouse Requirements Engineering
A Decision Based Approach

by Naveen Prakash,Deepika Prakash

  • Publisher : Springer
  • Release : 2018-01-29
  • Pages : 173
  • ISBN : 9811070199
  • Language : En, Es, Fr & De
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As the first to focus on the issue of Data Warehouse Requirements Engineering, this book introduces a model-driven requirements process used to identify requirements granules and incrementally develop data warehouse fragments. In addition, it presents an approach to the pair-wise integration of requirements granules for consolidating multiple data warehouse fragments. The process is systematic and does away with the fuzziness associated with existing techniques. Thus, consolidation is treated as a requirements engineering issue. The notion of a decision occupies a central position in the decision-based approach. On one hand, information relevant to a decision must be elicited from stakeholders; modeled; and transformed into multi-dimensional form. On the other, decisions themselves are to be obtained from decision applications. For the former, the authors introduce a suite of information elicitation techniques specific to data warehousing. This information is subsequently converted into multi-dimensional form. For the latter, not only are decisions obtained from decision applications for managing operational businesses, but also from applications for formulating business policies and for defining rules for enforcing policies, respectively. In this context, the book presents a broad range of models, tools and techniques. For readers from academia, the book identifies the scientific/technological problems it addresses and provides cogent arguments for the proposed solutions; for readers from industry, it presents an approach for ensuring that the product meets its requirements while ensuring low lead times in delivery.

The Integrated Data Hub, the Next Generation Data Warehouse

The Integrated Data Hub, the Next Generation Data Warehouse
The Smartest Way to Deal with the Data Integration Challenges

by Dario Mangano

  • Publisher : CreateSpace
  • Release : 2013-10-22
  • Pages : 286
  • ISBN : 9781481061407
  • Language : En, Es, Fr & De
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Data Warehouse projects fail. As an industry we have been battling with this phenomenon for decades. Though we have been getting better over the years, as an industry we still have a long way to go. Fortunately some people have found ways to beat the odds. By thinking out of the box, formulating new ideas, and creating new innovative approaches these people have each somehow unlocked the secrets of successful DW programs. Within this group there are those who have fire tested their theories with real life deployments. They have proven the merits of their ideas with perhaps the only test that really matters – actually deploying successful DW programs. Now this is a small group, a special club, and of the few members in this club, an even smaller group is willing and able to communicate and share their ideas. In this book, Integrated Data Hub™, Dario Mangano shares with us his ideas including the solution he developed and the proven architecture that he has successfully deployed in several organizations. This book is a guide to a successful data warehousing business intelligence (DWBI) program. One of the success factors is recognizing that there is no success to be found in a data warehouse project. To leverage enterprise data we have to recognize two things; first that the data warehouse is not a project with a beginning and end but rather an ongoing program, and second that this program is not technically driven but actually business and information driven. The Integrated Data Hub™ is an organizational information framework that takes into account the dynamic characteristics of the data warehouse function. Business alignment, data integration and historization are ongoing dynamic functions that need to respond to changes in the business, changes in the sources, and changes in downstream requirements. The organizational need for enterprise-wide data is an increasingly important component of enterprise management. With this increasing importance comes also an increasing need for traceability and auditability. Dario explains how the role of the business intelligence department is to manage the transformation of integrated and trusted data into understandable information with real business meaning. Dario's IDH leverages the concepts and principles of both Bill Inmon's data warehouse and corporate information factory, and of Ralph Kimball's dimensional modeling and data marts. Insofar as the goals of the IDH require an optimized modeling paradigm, Dario has specified the use of the data vault modeling approach. Dario starts by sketching the historical background and then introduces the IDH concept. Keep reading as Dario weaves the IDH components together into an effective strategy and a cohesive blueprint for enterprise information management. From a modeling perspective this book takes us from 3NF and Star Schemas to Data Vault and Dario's own Leaf Schemas. From an architectural perspective this book describes the component layers and their specific characteristics. This book is a great addition to the IP for the new age of data warehousing and information management. Data Warehouse programs using the IDH™ succeed. And perhaps that is the most compelling reason to read this book. Hans Hultgren (Author of the book: Modeling the Agile Data Warehouse with Data Vault)

Business Intelligence Tools for Small Companies

Business Intelligence Tools for Small Companies
A Guide to Free and Low-Cost Solutions

by Albert Nogués,Juan Valladares

  • Publisher : Apress
  • Release : 2017-05-25
  • Pages : 326
  • ISBN : 1484225686
  • Language : En, Es, Fr & De
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Learn how to transition from Excel-based business intelligence (BI) analysis to enterprise stacks of open-source BI tools. Select and implement the best free and freemium open-source BI tools for your company’s needs and design, implement, and integrate BI automation across the full stack using agile methodologies. Business Intelligence Tools for Small Companies provides hands-on demonstrations of open-source tools suitable for the BI requirements of small businesses. The authors draw on their deep experience as BI consultants, developers, and administrators to guide you through the extract-transform-load/data warehousing (ETL/DWH) sequence of extracting data from an enterprise resource planning (ERP) database freely available on the Internet, transforming the data, manipulating them, and loading them into a relational database. The authors demonstrate how to extract, report, and dashboard key performance indicators (KPIs) in a visually appealing format from the relational database management system (RDBMS). They model the selection and implementation of free and freemium tools such as Pentaho Data Integrator and Talend for ELT, Oracle XE and MySQL/MariaDB for RDBMS, and Qliksense, Power BI, and MicroStrategy Desktop for reporting. This richly illustrated guide models the deployment of a small company BI stack on an inexpensive cloud platform such as AWS. What You'll Learn You will learn how to manage, integrate, and automate the processes of BI by selecting and implementing tools to: Implement and manage the business intelligence/data warehousing (BI/DWH) infrastructure Extract data from any enterprise resource planning (ERP) tool Process and integrate BI data using open-source extract-transform-load (ETL) tools Query, report, and analyze BI data using open-source visualization and dashboard tools Use a MOLAP tool to define next year's budget, integrating real data with target scenarios Deploy BI solutions and big data experiments inexpensively on cloud platforms Who This Book Is For Engineers, DBAs, analysts, consultants, and managers at small companies with limited resources but whose BI requirements have outgrown the limitations of Excel spreadsheets; personnel in mid-sized companies with established BI systems who are exploring technological updates and more cost-efficient solutions

Information and Software Technologies

Information and Software Technologies
22nd International Conference, ICIST 2016, Druskininkai, Lithuania, October 13-15, 2016, Proceedings

by Giedre Dregvaite,Robertas Damasevicius

  • Publisher : Springer
  • Release : 2016-09-29
  • Pages : 768
  • ISBN : 3319462547
  • Language : En, Es, Fr & De
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This book constitutes the refereed proceedings of the 22nd International Conference on Information and Software Technologies, ICIST 2016, held in Druskininkai, Lithuania, in October 2016. The 61 papers presented were carefully reviewed and selected from 158 submissions. The papers are organized in topical sections on information systems; business intelligence for information and software systems; software engineering; information technology applications.

Advances in Databases and Information Systems

Advances in Databases and Information Systems
20th East European Conference, ADBIS 2016, Prague, Czech Republic, August 28-31, 2016, Proceedings

by Jaroslav Pokorný,Mirjana Ivanović,Bernhard Thalheim,Petr Šaloun

  • Publisher : Springer
  • Release : 2016-08-13
  • Pages : 354
  • ISBN : 331944039X
  • Language : En, Es, Fr & De
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This book constitutes the thoroughly refereed proceedings of the 20th East European Conference on Advances in Databases and Information Systems, ADBIS 2016, held in Prague, Czech Republic, in August 2016. The 21 full papers presented together with two keynote papers and one keynote abstract were carefully selected and reviewed from 85 submissions. The papers are organized in topical sections such as data quality, mining, analysis and clustering; model-driven engineering, conceptual modeling; data warehouse and multidimensional modeling, recommender systems; spatial and temporal data processing; distributed and parallel data processing; internet of things and sensor networks.