data science create teams that ask the right questions and deliver real value

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Data Science

Author : Doug Rose
ISBN : 9781484222539
Genre : Computers
File Size : 87. 5 MB
Format : PDF, ePub, Mobi
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Learn how to build a data science team within your organization rather than hiring from the outside. Teach your team to ask the right questions to gain actionable insights into your business. Most organizations still focus on objectives and deliverables. Instead, a data science team is exploratory. They use the scientific method to ask interesting questions and run small experiments. Your team needs to see if the data illuminate their questions. Then, they have to use critical thinking techniques to justify their insights and reasoning. They should pivot their efforts to keep their insights aligned with business value. Finally, your team needs to deliver these insights as a compelling story. Insight!: How to Build Data Science Teams that Deliver Real Business Value shows that the most important thing you can do now is help your team think about data. Management coach Doug Rose walks you through the process of creating and managing effective data science teams. You will learn how to find the right people inside your organization and equip them with the right mindset. The book has three overarching concepts: You should mine your own company for talent. You can’t change your organization by hiring a few data science superheroes. You should form small, agile-like data teams that focus on delivering valuable insights early and often. You can make real changes to your organization by telling compelling data stories. These stories are the best way to communicate your insights about your customers, challenges, and industry. What Your Will Learn: Create data science teams from existing talent in your organization to cost-efficiently extract maximum business value from your organization’s data Understand key data science terms and concepts Follow practical guidance to create and integrate an effective data science team with key roles and the responsibilities for each team member Utilize the data science life cycle (DSLC) to model essential processes and practices for delivering value Use sprints and storytelling to help your team stay on track and adapt to new knowledge Who This Book Is For Data science project managers and team leaders. The secondary readership is data scientists, DBAs, analysts, senior management, HR managers, and performance specialists.

Building Data Science Teams

Author : DJ Patil
ISBN : 9781449316778
Genre : Computers
File Size : 87. 59 MB
Format : PDF, Mobi
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As data science evolves to become a business necessity, the importance of assembling a strong and innovative data teams grows. In this in-depth report, data scientist DJ Patil explains the skills, perspectives, tools and processes that position data science teams for success. Topics include: What it means to be "data driven." The unique roles of data scientists. The four essential qualities of data scientists. Patil's first-hand experience building the LinkedIn data science team.

Enterprise Agility For Dummies

Author : Doug Rose
ISBN : 9781119446101
Genre : Business & Economics
File Size : 25. 74 MB
Format : PDF
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Manage and improve your organization's agile transformation Adopting an enterprise agile framework is a radical organizational change, and this book will help you get there without ever breaking a sweat. In Enterprise Agility For Dummies, you'll discover how to successfully choose and implement the right framework based on your organization's own unique culture. Organizational culture is one of the most overlooked challenges when trying to make a change to enterprise agile, and there are lots of resources out there that claim to have the perfect, one-size-fits-all solution. Luckily, this book takes a neutral stance and covers popular organizational change management techniques that you can implement to suit to your unique needs. Packed with step-by-step instruction and complemented with real-world case studies, this book offers everything you need to know in order to embrace a more agile mindset. Understand the benefits of an agile approach Pick the best enterprise agile framework for your organization Create a successful enterprise change management plan Let Enterprise Agility For Dummies help you optimize your business processes, and watch your productivity soar.

Building A Digital Analytics Organization

Author : Judah Phillips
ISBN : 9780133372816
Genre : Computers
File Size : 43. 59 MB
Format : PDF, Mobi
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Drive maximum business value from digital analytics, web analytics, site analytics, and business intelligence! In Building a Digital Analytics Organization, pioneering expert Judah Phillips thoroughly explains digital analytics to business practitioners, and presents best practices for using it to reduce costs and increase profitable revenue throughout the business. Phillips covers everything from making the business case through defining and executing strategy, and shows how to successfully integrate analytical processes, technology, and people in all aspects of operations. This unbiased and product-independent guide is replete with examples, many based on the author’s own extensive experience. Coverage includes: key concepts; focusing initiatives and strategy on business value, not technology; building an effective analytics organization; choosing the right tools (and understanding their limitations); creating processes and managing data; analyzing paid, owned, and earned digital media; performing competitive and qualitative analyses; optimizing and testing sites; implementing integrated multichannel digital analytics; targeting consumers; automating marketing processes; and preparing for the revolutionary “analytical economy.” For all business practitioners interested in analytics and business intelligence in all areas of the organization.

Big Data In Practice

Author : Bernard Marr
ISBN : 9781119231394
Genre : Business & Economics
File Size : 24. 34 MB
Format : PDF, Mobi
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The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter

Data Science

Author : Zacharias Voulgaris
ISBN : 1634622561
Genre :
File Size : 41. 99 MB
Format : PDF, Kindle
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Master the concepts and strategies underlying success and progress in data science. From the author of the bestsellers, Data Scientist and Julia for Data Science, this book covers four foundational areas of data science. The first area is the data science pipeline including methodologies and the data scientist's toolbox. The second are essential practices needed in understanding the data including questions and hypotheses. The third are pitfalls to avoid in the data science process. The fourth is an awareness of future trends and how modern technologies like Artificial Intelligence (AI) fit into the data science framework. The following chapters cover these four foundational areas: Chapter 1 - What Is Data Science? Chapter 2 - The Data Science Pipeline Chapter 3 - Data Science Methodologies Chapter 4 - The Data Scientist's Toolbox Chapter 5 - Questions to Ask and the Hypotheses They Are Based On Chapter 6 - Data Science Experiments and Evaluation of Their Results Chapter 7 - Sensitivity Analysis of Experiment Conclusions Chapter 8 - Programming Bugs Chapter 9 - Mistakes Through the Data Science Process Chapter 10 - Dealing with Bugs and Mistakes Effectively and Efficiently Chapter 11 - The Role of Heuristics in Data Science Chapter 12 - The Role of AI in Data Science Chapter 13 - Data Science Ethics Chapter 14 - Future Trends and How to Remain Relevant Targeted towards data science learners of all levels, this book aims to help the reader go beyond data science techniques and obtain a more holistic and deeper understanding of what data science entails. With a focus on the problems data science tries to solve, this book challenges the reader to become a self-sufficient player in the field.

Data For Business Performance

Author : Prashanth H Southekal, PhD
ISBN : 9781634621861
Genre : Computers
File Size : 67. 58 MB
Format : PDF, Mobi
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Today, digitization is dramatically changing the business landscape, and many progressive organizations have started to treat data as a valuable business asset. While many enterprises are investing in improved data management, only a few have leveraged data to truly impact business performance. To address this problem, Data for Business Performance provides readers with practical guidance and proven techniques to derive value from data in today’s business environment. Specifically, the book has five key elements that make it unique: The book is holistic, as it looks at deriving value for all three key purposes of data: decision making, compliance, and customer service. The book is for practitioners, with practical guidance and proven techniques supported by real world examples. The book is relevant for the current business and IT landscape. The book is novel, with the adoption of the Goal-Question-Metric (GQM) framework as the core mechanism to monetize data in the organization, based on business goals, key questions, and key performance indicators (KPIs). The book is technology-agnostic, as concepts are used for unlocking the value of data without any reference to proprietary technologies. This book is absolutely timely and relevant in today’s data-driven world. Most of the books on data available in the market today focus on data quality, governance, and analytics. This book from Dr. Prashanth Southekal is brilliant as it puts the business stakeholder at the center by addressing the key value propositions of the business user. This book is holistic and I strongly believe it will help to bridge the gaps we have today. Mario Faria Managing Vice President, Gartner, US In today’s era of digital transformation, data and information are more important than ever. But deep understanding of how to manage data and information properly is in short supply. That is what I love about this book by Dr. Southekal. He tangibly closes that gap for the reader. If you are using digital transformation to improve your business performance, this book and its discussion of data’s role in improving business performance is for you. Michael Fulton President, Americas Division, CC and C Solutions, US Packed with insights and leveraging a process oriented approach, this book covers a unique combination of the science, the art and the strategy of unlocking the potential of data for enterprises in a real-life context. The author has managed to provide a clear action plan for creating data analytics and its management a key function in a modern enterprise. Ashish Sonal (Vir Chakra) CEO, Orkash, India This book is one of the most practical sources for how companies can greatly improve their bottom line by improved data management and becoming a data-centric company. It combines leading data management theory with step-by-step implementation and real-life examples, and is a must-read for those wanting to derive more value from their corporate data. Lance Calleberg Application Architect, Husky Energy, Canada Certainly, an engaging read for both information management practitioners and business unit managers alike. The tools, models, and frameworks prescribed are valuable, relevant, and lucidly blend inputs from the real-world to address numerous data management glitches at organizations. Overall, a compelling read with several practical takeaways. Refreshing! Sriram Kannan Digital & Analytics Practice Leader, IBM, India Prashanth has given a very practical guide to implement data culture in an organization. The book Data for Business Performance talks about building the organization of the future and the role of data. Prashanth rightly believes and demonstrates that data is not an asset of the IT team and is an organization-wide asset. He proposes the need for the chief data officer (CDO) as a role that should anchor data and report to the CEO, and manage the stakeholders’ data needs. Harshajith Umapathy Senior Vice President, Hansa Cequity, India Dr. Southekal provides valuable insights on data and information management in mostly short and clearly written sections. Anyone interested in the data-driven company should read this book and learn about the hurdles on the road to be data-driven, and his valuable suggestions on how to overcome them. His wisdom may prevent some of the failures that helped him learn. Erik van der Voorden Domain Architect, Independent Consultant, Netherlands Data can tell us important stories when we process it by proven and structured approaches. Dr. Southekal’s book presents such an approach based on the GQM method for transforming business data into an enterprise asset. This book is a valuable resource for organizations willing to become real data-driven organizations. Ahmet Dikici, PhD Project Manager, Tubitak Bilgem Software Technologies, Turkey

Applied Business Analytics

Author : Nathaniel Lin
ISBN : 9780133481532
Genre : Business & Economics
File Size : 48. 91 MB
Format : PDF, ePub, Mobi
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Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll discover why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics… how to become one of those deciders… and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification.

Agile Data Science 2 0

Author : Russell Jurney
ISBN : 9781491960066
Genre : Computers
File Size : 45. 59 MB
Format : PDF, Kindle
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Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools. Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization. Build value from your data in a series of agile sprints, using the data-value pyramid Extract features for statistical models from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future via classification and regression Translate predictions into actions Get feedback from users after each sprint to keep your project on track

Principles Of Data Science

Author : Sinan Ozdemir
ISBN : 9781785888922
Genre : Computers
File Size : 34. 68 MB
Format : PDF
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Learn the techniques and math you need to start making sense of your data About This Book Enhance your knowledge of coding with data science theory for practical insight into data science and analysis More than just a math class, learn how to perform real-world data science tasks with R and Python Create actionable insights and transform raw data into tangible value Who This Book Is For You should be fairly well acquainted with basic algebra and should feel comfortable reading snippets of R/Python as well as pseudo code. You should have the urge to learn and apply the techniques put forth in this book on either your own data sets or those provided to you. If you have the basic math skills but want to apply them in data science or you have good programming skills but lack math, then this book is for you. What You Will Learn Get to know the five most important steps of data science Use your data intelligently and learn how to handle it with care Bridge the gap between mathematics and programming Learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results Build and evaluate baseline machine learning models Explore the most effective metrics to determine the success of your machine learning models Create data visualizations that communicate actionable insights Read and apply machine learning concepts to your problems and make actual predictions In Detail Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you'll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You'll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means. Style and approach This is an easy-to-understand and accessible tutorial. It is a step-by-step guide with use cases, examples, and illustrations to get you well-versed with the concepts of data science. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

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