Leading in Analytics: The Seven Critical Tasks for Executives to Master in the Age of Big Data

Leading in Analytics: The Critical Tasks for Executives to Master in the Age of Big Data is a step-by-step guide for business leaders who need to manage successful big data projects. It covers 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. It is drawn from best-practice research in the field of analytics and offers practical insight on how to get them right.

Format: Hardback
Length: 320 pages
Publication date: 26 October 2023
Publisher: John Wiley & Sons Inc

The importance of big data in today's business world cannot be overstated. As organizations collect and analyze more data than ever before, they are gaining valuable insights into their customers, products, and operations that can help them make informed decisions and drive growth. However, managing successful big data projects can be a daunting task for business leaders. In Leading in Analytics: The Critical Tasks for Executives to Master in the Age of Big Data, author and analytics expert John Sutter takes you through the entire process of guiding an analytics initiative from inception to execution.

The first step in leading a successful analytics project is to define the project's goals and objectives. This includes identifying the business problem that the project will address, determining the data that will be needed, and developing a strategic plan for how the data will be used. Once the project's goals and objectives have been defined, the next step is to assemble a team of experts who can help you execute the project. This team should include data scientists, analysts, and business experts who can bring different perspectives and skills to the project.

Gathering the right data is another critical task in leading a successful analytics project. This includes identifying the sources of data that are relevant to the project, acquiring the data, and ensuring that it is accurate and reliable. Once the data has been gathered, it must be analyzed and interpreted to draw meaningful insights. This involves using advanced analytics techniques such as machine learning, data mining, and predictive analytics to identify patterns and trends in the data.

Selecting the right tools is also an important task in leading a successful analytics project. This includes choosing tools that are compatible with the data and the analytics techniques that will be used, as well as tools that are easy to use and maintain. Once the tools have been selected, they must be integrated into the organization's existing systems and processes to ensure that the data can be accessed and analyzed efficiently.

Executing the strategic plan is the final step in leading a successful analytics project. This includes implementing the project's findings and recommendations, monitoring the project's progress, and making adjustments as needed. It is important to communicate the project's findings and recommendations to stakeholders throughout the organization to ensure that they are aware of the project's benefits and are able to use the data to make informed decisions.

In conclusion, managing successful big data projects requires a combination of technical skills and business expertise. By following the steps outlined in Leading in Analytics: The Critical Tasks for Executives to Master in the Age of Big Data, business leaders can ensure that their analytics initiatives are successful and that they are able to draw value from big data. By defining the project's goals and objectives, assembling a team of experts, gathering the right data, selecting the right tools, and executing the strategic plan, business leaders can ensure that their analytics initiatives are successful and that they are able to draw value from big data. By defining the project's goals and objectives, assembling a team of experts, gathering the right data, selecting the right tools, and executing the strategic plan, business leaders can ensure that their analytics initiatives are successful and that they are able to draw value from big data.

Weight: 804g
Dimension: 187 x 262 x 26 (mm)
ISBN-13: 9781119800415