HBR guide to data analytics basics for managers

By:

Harvard Business Review Press

Material type: Text

TextPublication details: Harvard Business Review Press Boston 2018Description: x, 231 pISBN:

9781633694286

Subject(s):

Data analytics

DDC classification:

658.4033 HAR

Summary: Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started? Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others. You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes

List(s) this item appears in: IT & Decision Sciences | HR & OB

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	658.4033 HAR (Browse shelf(Opens below))	1	Available		000602

Today's business environment brings with it an onslaught of data. Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?

Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.

You'll learn how to:

Identify the metrics you need to measure
Run experiments and A/B tests
Ask the right questions of your data experts
Understand statistical terms and concepts
Create effective charts and visualizations
Avoid common mistakes

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