Democratizing Analytics
DOWNLOAD
Download Democratizing Analytics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Democratizing Analytics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Democratizing Analytics
DOWNLOAD
Author : Melissa Burroughs
language : en
Publisher:
Release Date : 2023
Democratizing Analytics written by Melissa Burroughs and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Data mining categories.
Today, enterprises have more data at their disposal than ever before. Yet relatively few companies can quickly and efficiently get data to the people who need it for critical insights and important decisions. In this insightful report, David Sweenor and Melissa Burroughs from Alteryx explain analytic democratization, a strategy that leading organizations are now using to manage data access, analytics platforms, and data-driven decision-making. By democratizing analytics, you can enable all people within your business to create and leverage data-driven insights quickly and effectively. This self-service approach frees IT and data science personnel to focus on high-value initiatives. You'll learn how empowering knowledge workers with analytic access will benefit your business through optimized processes, faster translation of needs into solutions, and greater innovation.
Democratizing Our Data
DOWNLOAD
Author : Julia Lane
language : en
Publisher: MIT Press
Release Date : 2021-10-19
Democratizing Our Data written by Julia Lane and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-19 with Political Science categories.
A wake-up call for America to create a new framework for democratizing data. Public data are foundational to our democratic system. People need consistently high-quality information from trustworthy sources. In the new economy, wealth is generated by access to data; government's job is to democratize the data playing field. Yet data produced by the American government are getting worse and costing more. In Democratizing Our Data, Julia Lane argues that good data are essential for democracy. Her book is a wake-up call to America to fix its broken public data system.
Big Data Democratized Analytics And Deep Context Will Change How We Think And Do Development
DOWNLOAD
Author :
language : en
Publisher:
Release Date :
Big Data Democratized Analytics And Deep Context Will Change How We Think And Do Development written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
I provide a synopsis of the most impactful developments in three key areas: the base (data) layer, the analysis layer, and the feedback (data) layer. [...] To date international institutions have made the most progress towards data openness, select public sector authorities (for instance under the purview of the Open Government Partnership) are also making progress, but it is the private sector - the main repository of "big data" - that is the holy grail. [...] This is truly big data and its growth has exploded off the charts thanks in large part to the explosion of mobile sensors (the most important of which is the mobile phone but think also credit cards, laptops, GPS and everything from radio-frequency to QR codes), and the rapid democratization of high-power analytics. [...] The point is the rapid emergence of altogether new data-streams, in step with the development of analytical capacity to draw useful inference out of them. [...] To understand how powerful the feedback layer can be consider the experience of the Mobile Accord, which at the initiative of the World Bank's World Development Report 2011, ran Geo Poll an SMS based targeted polling in the DRC.
Democratizing Business Analytics Audio Book
DOWNLOAD
Author : Ben Lorica
language : en
Publisher:
Release Date : 2016
Democratizing Business Analytics Audio Book written by Ben Lorica and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
In this episode of the O'Reilly Data Show, Ben Lorica speaks with one of Strata + Hadoop World's most popular teachers-Duncan Ross, data and analytics director at TES Global. In his long career in data, Ross has seen several stages of the evolution of tools, techniques, and training programs, and along the way he has interacted with business managers in many countries and regions. In keeping with his wide-ranging interests, Ben and Duncan discuss many topics, including business analytics, data science training programs, data philanthropy and data for good, and university rankings.
The Analytics Lifecycle Toolkit
DOWNLOAD
Author : Gregory S. Nelson
language : en
Publisher: John Wiley & Sons
Release Date : 2018-04-03
The Analytics Lifecycle Toolkit written by Gregory S. Nelson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-03 with Business & Economics categories.
Data has become the new currency; organizations are drowning in it, but few are cashing in on its true value. The Analytics Lifecycle Toolkit translates the entire analytics lifecycle into actionable insights, providing a framework for building an effective analytics capability and the processes that turn data into action. Part 1 describes the “who,” “how,” and “why” of modern enterprise analytics, giving leaders clear insight into the value of strategically-aligned capabilities. Part 2 details best practices that include problem framing, data sensemaking, model development, change management, data management, product management, and more. Part 3 rounds out the discussion by providing guidance on sustaining high performance and guiding the analytics function into new phases of business. For organizations who see the value of analytics but lack the depth of knowledge needed to structure appropriate solutions, this book breaks the cycle of frustration and provides a roadmap for putting the right people, processes, and technologies into place. For those who have already implemented analytics, this book serves as a reference for leadership and a “refresher course” to update the team on the latest in practices and processes. Rather than a simple catalogue of analytics models, the discussion emphasizes underlying principles in key process areas to help organizations build analytics capabilities tailored to their specific needs—allowing them to harvest the highest-value information to better inform strategic decisions. In line with the book’s practical focus, the companion website provides downloadable resources, tools, videos, and more to support and streamline implementation. The discussion itself assumes no prior knowledge of analytics and explicitly clarifies complex concepts and terms, using real-world examples to illustrate what effective practice looks like on the ground. With clear guidance, expert insight, and a wealth of practical tools, The Analytics Lifecycle Toolkit is an essential resource for any organization seeking an optimized analytics program.
The Self Service Data Roadmap
DOWNLOAD
Author : Sandeep Uttamchandani
language : en
Publisher:
Release Date : 2020-10-13
The Self Service Data Roadmap written by Sandeep Uttamchandani and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-13 with categories.
The world's most valuable resource is data. Companies across all industry verticals are using data-driven insights as a key competitive advantage. But the time required for transforming raw data to insights can take days or weeks when you want it in minutes or hours. Data scientists spend nearly 80% of their time in data engineering, rather than developing insights. And most organizations can't scale their data science teams fast enough to keep up with growing business needs for better, faster insights. This book will help data engineers, data scientists, and data team managers address these issues by building a self-service data science platform that democratizes the ability to extract insights from the data to everyone in the organization. Data scientists, software engineers, product managers, and marketers can use it to discover, transform, and analyze data and publish automated insights in production. This book is not: A deep dive into the "shiny new" technologies, or any one specific technology A silver bullet technology for building a self-service portal. Organizations differ in their maturity, people, process, and technology and require tailored solutions This book is: A collection of must-have operational capabilities for building a self-service data portal A blueprint for achieving better and faster insights A process for democratizing data engineering expertise across an organization A practical and indispensable guide for any decision-maker, implementer, or strategist working with an organization's data science platform.
Advanced Analytics With Power Bi And Excel
DOWNLOAD
Author : Dejan Sarka
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2023-10-13
Advanced Analytics With Power Bi And Excel written by Dejan Sarka and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-13 with Computers categories.
Empowering You to Master Business Intelligence and Solve Real-world Analytical Problems. KEY FEATURES ● Fulfill your business analytics objectives through comprehensive theory and hands-on, real-world examples. ● Dive into the world of advanced Business Intelligence using data science with Power BI. ● Acquire in-demand skills that align with the current job market and enhance your career prospects. DESCRIPTION In today's analytics landscape, proficiency in Excel and Power BI is practically a prerequisite for a successful career. This book provides a concise yet comprehensive exploration of these foundational elements of modern Business Intelligence (BI). Comprising ten chapters, this book covers the entire development journey of a Power BI analytical solution, spanning from data modeling and preparation to report creation, publication, and dashboard and app deployment. It offers insights into security measures and performance optimization, ensuring a well-rounded understanding of the BI ecosystem. Furthermore, it delves into advanced topics, such as leveraging data science algorithms within reports, offering readers an extensive learning experience. The book takes a holistic approach to these technologies, offering a contrast to the narrow perspectives often adopted by contemporary BI professionals who rely solely on a single tool or language. The book allows data enrichment through calculations that can be achieved using various languages, including SQL queries at the source, Power Query Formula Language, M, Python, R, and DAX. By the end of this book you will master these options but be able to also weigh their pros and cons to make informed decisions. WHAT WILL YOU LEARN ● Learn the art of crafting comprehensive reports and analyses using Excel and Power BI. ● Discover efficient methods for sharing your insights and reports with your team or clients. ● Gain the skills to maintain and update your analytical solutions effectively. ● Understand the significance of extracting valuable information from data in today's business landscape. ● Address the increasing demand for skilled analysts, filling a critical gap in the industry. ● Dive into numerous real-world examples to develop a strong foundation in analytical techniques. WHO IS THIS BOOK FOR? This book caters to aspiring Business Intelligence developers, analysts seeking to enhance their skills, and beginners looking to efficiently use tools like Excel. It also appeals to data enthusiasts and serves as a practical resource for students and educators in data-related fields. If you are a professional from the industry interested in leveraging Power BI and Excel for data-driven decision-making, this book is for you. TABLE OF CONTENTS 1. Introducing the Theoretical Background for Democratizing Analytics 2. Acquiring and transforming data from multiple sources 3. Power Query Transformations and Formula Language (M) Overview 4. Building a simple analytical solution with Power Pivot in Excel 5. Enhancing the model and business analysis with DAX 6. Creating reports in Power BI Desktop 7. Using the Power BI Service 8. Data Science in Power BI 9. Optimizing Power BI models and reports 10. Deploying, Maintaining, and Securing Power BI Assets Index
Implementing Analytics
DOWNLOAD
Author : Nauman Sheikh
language : en
Publisher: Newnes
Release Date : 2013-05-06
Implementing Analytics written by Nauman Sheikh and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-06 with Computers categories.
Implementing Analytics demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization. Implementing Analytics simplifies and helps democratize a very specialized discipline to foster business efficiency and innovation without investing in multi-million dollar technology and manpower. A technology agnostic methodology that breaks down complex tasks like model design and tuning and emphasizes business decisions rather than the technology behind analytics. Simplifies the understanding of analytics from a technical and functional perspective and shows a wide array of problems that can be tackled using existing technology Provides a detailed step by step approach to identify opportunities, extract requirements, design variables and build and test models. It further explains the business decision strategies to use analytics models and provides an overview for governance and tuning Helps formalize analytics projects from staffing, technology and implementation perspectives Emphasizes machine learning and data mining over statistics and shows how the role of a Data Scientist can be broken down and still deliver the value by building a robust development process
Fundamentals Of Analytics Engineering
DOWNLOAD
Author : Dumky De Wilde
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29
Fundamentals Of Analytics Engineering written by Dumky De Wilde and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Computers categories.
Gain a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering Key Features Discover how analytics engineering aligns with your organization's data strategy Access insights shared by a team of seven industry experts Tackle common analytics engineering problems faced by modern businesses Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWritten by a team of 7 industry experts, Fundamentals of Analytics Engineering will introduce you to everything from foundational concepts to advanced skills to get started as an analytics engineer. After conquering data ingestion and techniques for data quality and scalability, you’ll learn about techniques such as data cleaning transformation, data modeling, SQL query optimization and reuse, and serving data across different platforms. Armed with this knowledge, you will implement a simple data platform from ingestion to visualization, using tools like Airbyte Cloud, Google BigQuery, dbt, and Tableau. You’ll also get to grips with strategies for data integrity with a focus on data quality and observability, along with collaborative coding practices like version control with Git. You’ll learn about advanced principles like CI/CD, automating workflows, gathering, scoping, and documenting business requirements, as well as data governance. By the end of this book, you’ll be armed with the essential techniques and best practices for developing scalable analytics solutions from end to end.What you will learn Design and implement data pipelines from ingestion to serving data Explore best practices for data modeling and schema design Scale data processing with cloud based analytics platforms and tools Understand the principles of data quality management and data governance Streamline code base with best practices like collaborative coding, version control, reviews and standards Automate and orchestrate data pipelines Drive business adoption with effective scoping and prioritization of analytics use cases Who this book is for This book is for data engineers and data analysts considering pivoting their careers into analytics engineering. Analytics engineers who want to upskill and search for gaps in their knowledge will also find this book helpful, as will other data professionals who want to understand the value of analytics engineering in their organization's journey toward data maturity. To get the most out of this book, you should have a basic understanding of data analysis and engineering concepts such as data cleaning, visualization, ETL and data warehousing.
Automating Data Quality Monitoring
DOWNLOAD
Author : Jeremy Stanley
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-01-09
Automating Data Quality Monitoring written by Jeremy Stanley and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-09 with Computers categories.
The world's businesses ingest a combined 2.5 quintillion bytes of data every day. But how much of this vast amount of data--used to build products, power AI systems, and drive business decisions--is poor quality or just plain bad? This practical book shows you how to ensure that the data your organization relies on contains only high-quality records. Most data engineers, data analysts, and data scientists genuinely care about data quality, but they often don't have the time, resources, or understanding to create a data quality monitoring solution that succeeds at scale. In this book, Jeremy Stanley and Paige Schwartz from Anomalo explain how you can use automated data quality monitoring to cover all your tables efficiently, proactively alert on every category of issue, and resolve problems immediately. This book will help you: Learn why data quality is a business imperative Understand and assess unsupervised learning models for detecting data issues Implement notifications that reduce alert fatigue and let you triage and resolve issues quickly Integrate automated data quality monitoring with data catalogs, orchestration layers, and BI and ML systems Understand the limits of automated data quality monitoring and how to overcome them Learn how to deploy and manage your monitoring solution at scale Maintain automated data quality monitoring for the long term