Agile Analytics
Agile Analytics

Author: Ken Collier

Publisher: Addison-Wesley

Published: 2012

Total Pages: 368

ISBN-13: 032150481X

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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.

Analytics
Analytics

Author: Phil Simon

Publisher: John Wiley & Sons

Published: 2017-07-03

Total Pages: 304

ISBN-13: 1119424208

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For years, organizations have struggled to make sense out of their data. IT projects designed to provide employees with dashboards, KPIs, and business-intelligence tools often take a year or more to reach the finish line...if they get there at all. This has always been a problem. Today, though, it's downright unacceptable. The world changes faster than ever. Speed has never been more important. By adhering to antiquated methods, firms lose the ability to see nascent trends—and act upon them until it's too late. But what if the process of turning raw data into meaningful insights didn't have to be so painful, time-consuming, and frustrating? What if there were a better way to do analytics? Fortunately, you're in luck... Analytics: The Agile Way is the eighth book from award-winning author and Arizona State University professor Phil Simon. Analytics: The Agile Way demonstrates how progressive organizations such as Google, Nextdoor, and others approach analytics in a fundamentally different way. They are applying the same Agile techniques that software developers have employed for years. They have replaced large batches in favor of smaller ones...and their results will astonish you. Through a series of case studies and examples, Analytics: The Agile Way demonstrates the benefits of this new analytics mind-set: superior access to information, quicker insights, and the ability to spot trends far ahead of your competitors.

Agile Data Science
Agile Data Science

Author: Russell Jurney

Publisher: "O'Reilly Media, Inc."

Published: 2013-10-15

Total Pages: 269

ISBN-13: 1449326919

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Mining big data requires a deep investment in people and time. How can you be sure you’re building the right models? With this hands-on book, you’ll learn a flexible toolset and methodology for building effective analytics applications with Hadoop. Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you. All example code in this book is available as working Heroku apps. Create analytics applications by using the agile big data development methodology Build value from your data in a series of agile sprints, using the data-value stack Gain insight by using several data structures to extract multiple features from a single dataset Visualize data with charts, and expose different aspects through interactive reports Use historical data to predict the future, and translate predictions into action Get feedback from users after each sprint to keep your project on track

Lean Analytics
Lean Analytics

Author: Alistair Croll

Publisher: "O'Reilly Media, Inc."

Published: 2024-02-23

Total Pages: 403

ISBN-13: 1098168151

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Whether you're a startup founder trying to disrupt an industry or an entrepreneur trying to provoke change from within, your biggest challenge is creating a product people actually want. Lean Analytics steers you in the right direction. This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without. Understand Lean Startup, analytics fundamentals, and the data-driven mindset Look at six sample business models and how they map to new ventures of all sizes Find the One Metric That Matters to you Learn how to draw a line in the sand, so you'll know it's time to move forward Apply Lean Analytics principles to large enterprises and established products

Actionable Agile Metrics for Predictability
Actionable Agile Metrics for Predictability

Author: Daniel S. Vacanti

Publisher:

Published: 2015-03-04

Total Pages: 314

ISBN-13: 9780986436338

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"When will it be done?" That is probably the first question your customers ask you once you start working on something for them. Think about how many times you have been asked that question. How many times have you ever actually been right? We can debate all we want whether this is a fair question to ask given the tremendous amount of uncertainty in knowledge work, but the truth of the matter is that our customers are going to inquire about completion time whether we like it or not. Which means we need to come up with an accurate way to answer them. The problem is that the forecasting tools that we currently utilize have made us ill-equipped to provide accurate answers to reasonable customer questions. Until now. Topics Include Why managing for flow is the best strategy for predictability-including an introduction to Little's Law and its implications for flow. A definition of the basic metrics of flow and how to properly visualize those metrics in analytics like Cumulative Flow Diagrams and Scatterplots. Why your process policies are the potentially the biggest reason that you are unpredictable.

Monetizing Your Data
Monetizing Your Data

Author: Andrew Roman Wells

Publisher: John Wiley & Sons

Published: 2017-02-23

Total Pages: 370

ISBN-13: 1119356261

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Transforming data into revenue generating strategies and actions Organizations are swamped with data—collected from web traffic, point of sale systems, enterprise resource planning systems, and more, but what to do with it? Monetizing your Data provides a framework and path for business managers to convert ever-increasing volumes of data into revenue generating actions through three disciplines: decision architecture, data science, and guided analytics. There are large gaps between understanding a business problem and knowing which data is relevant to the problem and how to leverage that data to drive significant financial performance. Using a proven methodology developed in the field through delivering meaningful solutions to Fortune 500 companies, this book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions. Beginning with an explanation of the analytical cycle, this book guides you through the process of developing value generating strategies that can translate into big returns. The companion website, www.monetizingyourdata.com, provides templates, checklists, and examples to help you apply the methodology in your environment, and the expert author team provides authoritative guidance every step of the way. This book shows you how to use your data to: Monetize your data to drive revenue and cut costs Connect your data to decisions that drive action and deliver value Develop analytic tools to guide managers up and down the ladder to better decisions Turning data into action is key; data can be a valuable competitive advantage, but only if you understand how to organize it, structure it, and uncover the actionable information hidden within it through decision architecture and guided analytics. From multinational corporations to single-owner small businesses, companies of every size and structure stand to benefit from these tools, methods, and techniques; Monetizing your Data walks you through the translation and transformation to help you leverage your data into value creating strategies.

Agile Data Science 2.0
Agile Data Science 2.0

Author: Russell Jurney

Publisher: "O'Reilly Media, Inc."

Published: 2017-06-07

Total Pages: 351

ISBN-13: 1491960086

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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

Agile Estimating and Planning
Agile Estimating and Planning

Author: Mike Cohn

Publisher: Pearson Education

Published: 2005-11-01

Total Pages: 526

ISBN-13: 0132703106

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Agile Estimating and Planning is the definitive, practical guide to estimating and planning agile projects. In this book, Agile Alliance cofounder Mike Cohn discusses the philosophy of agile estimating and planning and shows you exactly how to get the job done, with real-world examples and case studies. Concepts are clearly illustrated and readers are guided, step by step, toward how to answer the following questions: What will we build? How big will it be? When must it be done? How much can I really complete by then? You will first learn what makes a good plan-and then what makes it agile. Using the techniques in Agile Estimating and Planning, you can stay agile from start to finish, saving time, conserving resources, and accomplishing more. Highlights include: Why conventional prescriptive planning fails and why agile planning works How to estimate feature size using story points and ideal days–and when to use each How and when to re-estimate How to prioritize features using both financial and nonfinancial approaches How to split large features into smaller, more manageable ones How to plan iterations and predict your team's initial rate of progress How to schedule projects that have unusually high uncertainty or schedule-related risk How to estimate projects that will be worked on by multiple teams Agile Estimating and Planning supports any agile, semiagile, or iterative process, including Scrum, XP, Feature-Driven Development, Crystal, Adaptive Software Development, DSDM, Unified Process, and many more. It will be an indispensable resource for every development manager, team leader, and team member.

Data Analytics in Project Management
Data Analytics in Project Management

Author: Seweryn Spalek

Publisher: Taylor & Francis Group/CRC Press

Published: 2019-01-01

Total Pages: 11

ISBN-13: 1138307289

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Data Analytics in Project Management. Data analytics plays a crucial role in business analytics. Without a rigid approach to analyzing data, there is no way to glean insights from it. Business analytics ensures the expected value of change while that change is implemented by projects in the business environment. Due to the significant increase in the number of projects and the amount of data associated with them, it is crucial to understand the areas in which data analytics can be applied in project management. This book addresses data analytics in relation to key areas, approaches, and methods in project management. It examines: • Risk management • The role of the project management office (PMO) • Planning and resource management • Project portfolio management • Earned value method (EVM) • Big Data • Software support • Data mining • Decision-making • Agile project management Data analytics in project management is of increasing importance and extremely challenging. There is rapid multiplication of data volumes, and, at the same time, the structure of the data is more complex. Digging through exabytes and zettabytes of data is a technological challenge in and of itself. How project management creates value through data analytics is crucial. Data Analytics in Project Management addresses the most common issues of applying data analytics in project management. The book supports theory with numerous examples and case studies and is a resource for academics and practitioners alike. It is a thought-provoking examination of data analytics applications that is valuable for projects today and those in the future.

Lean Project Management
Lean Project Management

Author: Philip Small

Publisher: Philip Small

Published: 2022-02-20

Total Pages: 545

ISBN-13:

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This Is How The World's Top Tech Companies Manage Their Projects - Use Their Methods And Let Your Startup Thrive! This book includes: Lean Startup, Lean Enterprise, Lean Analytics, Agile Project Management, Lean Six Sigma, Kaizen Do you want to run your small business using the same strategies as the leaders in your field? Do you want to have a clear advantage over your competitors? Do you want your customers to be happy and eager to pay you even more? It's time to learn Lean. With Lean Project Management, you can create highquality products in less time. You can manage projects in a way that actually empowers and motivates your employees. Last but not least, your customers will LOVE working with you if your company uses Lean and Agile methods. This book will show you how to implement Lean methods in your startup and take it to the next level. With this book, you will: Learn the step-by-step process of managing Lean projects Maximize your team's productivity with Scrum Visualize your workflows with Kanban Understand Lean Six Sigma roles and management boards Explore The 5S system - pros and cons Use Lean Analytics to measure the things that matter Adopt the Kaizen mindset to encourage growth and positive change Grow and scale your thriving business! The Lean mindset is your key to maximum productivity and genuine leadership. It's your key to innovation and success (and making more money in the process). You can use it to manage everything from your personal projects to a thriving corporation - Lean is scalable, flexible, and empowering. In fact, Lean Project Management can be used in all fields and industries - so dive in and transform your business now! Get your hands on this book before your competitors do. Get Your Copy Now!