Self-Service Analytics Simplified PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Self-Service Analytics Simplified PDF full book. Access full book title Self-Service Analytics Simplified by Arshad Khan. Download full books in PDF and EPUB format.
Author: Arshad Khan
Publisher: Khan Consulting & Publishing LLC
ISBN: 0966086376
Category : Computers
Languages : en
Pages : 176
Get Book Here
Book Description
Self-Service Analytics Simplified: How to Plan and Implement will introduce you to self-service analytics (SSA), which aims to make business users less dependent on IT for their reporting and analytics needs. This book, which teaches how to plan and implement an SSA project, will appeal to a broad range of users including senior executives, business and IT managers, project managers, data analysts, business analysts, developers, casual users, as well as IT professionals. The topics covered in Self-Service Analytics Simplified: How to Plan and Implement include an introduction to self-service analytics, relationship with BI, benefits for different types of users, readiness assessment, planning, data-related topics including metadata and data pipelining, architecture, tools, requirements, implementation, data governance, security, training, data and user onboarding, and barriers to adoption, as well as challenges, best practices, lessons, and tips.
Author: Arshad Khan
Publisher: Khan Consulting & Publishing LLC
ISBN: 0966086376
Category : Computers
Languages : en
Pages : 176
Get Book Here
Book Description
Self-Service Analytics Simplified: How to Plan and Implement will introduce you to self-service analytics (SSA), which aims to make business users less dependent on IT for their reporting and analytics needs. This book, which teaches how to plan and implement an SSA project, will appeal to a broad range of users including senior executives, business and IT managers, project managers, data analysts, business analysts, developers, casual users, as well as IT professionals. The topics covered in Self-Service Analytics Simplified: How to Plan and Implement include an introduction to self-service analytics, relationship with BI, benefits for different types of users, readiness assessment, planning, data-related topics including metadata and data pipelining, architecture, tools, requirements, implementation, data governance, security, training, data and user onboarding, and barriers to adoption, as well as challenges, best practices, lessons, and tips.
Author: Sandeep Uttamchandani
Publisher: "O'Reilly Media, Inc."
ISBN: 1492075205
Category : Computers
Languages : en
Pages : 297
Get Book Here
Book Description
Data-driven insights are a key competitive advantage for any industry today, but deriving insights from raw data can still take days or weeks. Most organizations can’t scale data science teams fast enough to keep up with the growing amounts of data to transform. What’s the answer? Self-service data. With this practical book, data engineers, data scientists, and team managers will learn how to build a self-service data science platform that helps anyone in your organization extract insights from data. Sandeep Uttamchandani provides a scorecard to track and address bottlenecks that slow down time to insight across data discovery, transformation, processing, and production. This book bridges the gap between data scientists bottlenecked by engineering realities and data engineers unclear about ways to make self-service work. Build a self-service portal to support data discovery, quality, lineage, and governance Select the best approach for each self-service capability using open source cloud technologies Tailor self-service for the people, processes, and technology maturity of your data platform Implement capabilities to democratize data and reduce time to insight Scale your self-service portal to support a large number of users within your organization
Author: Ralph Kimball
Publisher: John Wiley & Sons
ISBN: 1118082141
Category : Computers
Languages : en
Pages : 464
Get Book Here
Book Description
This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts.
Author: Annu Roy
Publisher: BPB Publications
ISBN: 935551820X
Category : Computers
Languages : en
Pages : 342
Get Book Here
Book Description
Transform raw data into actionable insights by collecting, cleaning, analyzing, and visualizing data KEY FEATURES ● Use data analytics to create insights that drive better decision making. ● Create interactive visualizations that communicate data insights to stakeholders. ● Use visualizations to communicate the findings of your analysis in a way that is easy to understand and interpret. DESCRIPTION Data-driven culture is becoming increasingly important in modern enterprises, and self-service BI tools are making it easier for professionals to gain insights from data. This book serves as a practical and invaluable guide for all data-driven users, empowering them to gain insights rapidly and effortlessly, thereby enabling organizations to unlock the true potential of their data. This book is a practical guide that teaches readers how to use self-service BI tools to organize, clean, and analyze data. It offers step-by-step instructions on connecting to and refining data from various sources, including data lakes, data warehouses, cloud applications, and spreadsheets, including platforms such as Snowflake or Amazon Redshift. The book also provides expert guidance on smart data preparation and data discovery techniques, equipping you with a comprehensive understanding of all the capabilities and features of Power BI. Through practical examples, you will learn how to run, design, and test a wide array of analytics, along with insightful visualizations, heatmaps, and reports. By the end of the book, you will be able to use self-service BI tools to conduct analysis and generate data-driven business reports without any technical skills. WHAT YOU WILL LEARN ● Discover, combine, and transform data from various sources using Power Query. ● Learn how to create and manage data models in Power BI. ● Create a range of visualizations in Power BI, including charts, tables, and maps. ● Understand how to create, analyze, and share interactive reports in Power BI. ● Leverage Power BI Premium features to handle large datasets proficiently. WHO THIS BOOK IS FOR This book is for anyone who wants to learn about data analytics, regardless of their current role or experience level. TABLE OF CONTENTS 1. Getting Started with Power BI 2. Data Discovery Using Power Query 3. Data Modeling in Power BI 4. Visualizing Data in Power BI 5. Managing Reports in Power BI Service 6. Working with Large Data Volumes 7. DAX Reference Guide 8. Use Case - Creating a Risk Report in Power BI Epilogue Knowledge Check Answers
Author: Arshad Khan
Publisher:
ISBN: 9781936420322
Category : Computers
Languages : en
Pages : 0
Get Book Here
Book Description
This book targets business and IT professionals who need an introduction to business intelligence and data warehousing fundamentals through a simple question / answer format. Topics include evolution and fundamentals, characteristics and process, architecture and objects, metadata, data conversion, ETL, data storage, infrastructure, data access, data marts, implementation approaches, planning, design, Inmon vs. Kimball, multi-dimensionality, OLAP, facts and dimensions, common mistakes and tips, trends, etc.
Author: Nathan E. Myers
Publisher: John Wiley & Sons
ISBN: 1119773318
Category : Business & Economics
Languages : en
Pages : 352
Get Book Here
Book Description
Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands.
Author: Evan Stubbs
Publisher: John Wiley & Sons
ISBN: 1118370562
Category : Business & Economics
Languages : en
Pages : 368
Get Book Here
Book Description
AVOID THE MISTAKES THAT OTHERS MAKE – LEARN WHAT LEADS TO BEST PRACTICE AND KICKSTART SUCCESS This groundbreaking resource provides comprehensive coverage across all aspects of business analytics, presenting proven management guidelines to drive sustainable differentiation. Through a rich set of case studies, author Evan Stubbs reviews solutions and examples to over twenty common problems spanning managing analytics assets and information, leveraging technology, nurturing skills, and defining processes. Delivering Business Analytics also outlines the Data Scientist’s Code, fifteen principles that when followed ensure constant movement towards effective practice. Practical advice is offered for addressing various analytics issues; the advantages and disadvantages of each issue’s solution; and how these solutions can optimally create organizational value. With an emphasis on real-world examples and pragmatic advice throughout, Delivering Business Analytics provides a reference guide on: The economic principles behind how business analytics leads to competitive differentiation The elements which define best practice The Data Scientist’s Code, fifteen management principles that when followed help teams move towards best practice Practical solutions and frequent missteps to twenty-four common problems across people and process, systems and assets, and data and decision-making Drawing on the successes and failures of countless organizations, author Evan Stubbs provides a densely packed practical reference on how to increase the odds of success in designing business analytics systems and managing teams of data scientists. Uncover what constitutes best practice in business analytics and start achieving it with Delivering Business Analytics.
Author: Chiara Ghidini
Publisher: Springer Nature
ISBN: 3030307964
Category : Computers
Languages : en
Pages : 583
Get Book Here
Book Description
The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community. The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track. The chapter "The SEPSES knowledge graph: An integrated resource for cybersecurity" is open access under a CC BY 4.0 license at link.springer.com.
Author: Juan Sequeda
Publisher: Springer Nature
ISBN: 3031019164
Category : Computers
Languages : en
Pages : 142
Get Book Here
Book Description
This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.
Author: Thomas W. Dinsmore
Publisher: Apress
ISBN: 1484213114
Category : Computers
Languages : en
Pages : 276
Get Book Here
Book Description
Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
