Leading in Analytics
The Seven Critical Tasks for Executives to Master in the Age of Big Data
Joseph A. Cazier
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Leading in Analytics
The Seven Critical Tasks for Executives to Master in the Age of Big Data
Joseph A. Cazier
About This Book
A step-by-step guide for business leaders who need to manage successful big data projects
Leading in Analytics: The Critical Tasks for Executives to Master in the Age of Big Data takes you through the entire process of guiding an analytics initiative from inception to execution. You'll learn which aspects of the project to pay attention to, the right questions to ask, and how to keep the project team focused on its mission to produce relevant and valuable project. As an executive, you can't control every aspect of the process. But if you focus on high-impact factors that you can control, you can ensure an effective outcome. This book describes those factors and offers practical insight on how to get them right.
Drawn from best-practice research in the field of analytics, the Manageable Tasks described in this book are specific to the goal of implementing big data tools at an enterprise level. A dream team of analytics and business experts have contributed their knowledge to show you how to choose the right business problem to address, put together the right team, gather the right data, select the right tools, and execute your strategic plan to produce an actionable result. Become an analytics-savvy executive with this valuable book.
- Ensure the success of analytics initiatives, maximize ROI, and draw value from big data
- Learn to define success and failure in analytics and big data projects
- Set your organization up for analytics success by identifying problems that have big data solutions
- Bring together the people, the tools, and the strategies that are right for the job
By learning to pay attention to critical tasks in every analytics project, non-technical executives and strategic planners can guide their organizations to measurable results.