Master Data Management

Big Data in Project Management: How Crucial Is it?

Studies reveal that harnessing the power of big data can increase your operational margin by 60%. This means leveraging big data can help you efficiently run your project workflows and processes. Furthermore, an in-depth understanding of big data enables you to identify the right approach for project management. It allows you to gain actionable insights into tools to process, analyze, and transform information to enhance your project process. In this article at TDWI, Stan Pugsley explains the impact of big data in project management.

Benefits of Big Data in Project Management

Reduces Complexity

Inefficient processes or inadequate knowledge can add to the complexity of project management. However, using robust project management software to streamline the project and analyze big data can help you uncover project challenges and issues. Additionally, you can analyze project information, resolve problems, and simplify workflow bottlenecks with big data tools.

Big Data in Project Management Lowers Costs

Big data analytics is about collecting more data to predict future events and trends within your industry. You can make your resource forecasting and planning processes more efficient with relevant data. In addition, you can determine the right budget, estimates, and cost-effective project implementation. Additionally, you should be able to reduce the project inaccuracies that set back your operations for months.

Boosts Risk Management

Big data allows you to regularly identify and manage your project risks. Data analytics will enable you to minimize the risks’ impact on your processes and results. With the help of big data, you can develop the right methods and use the right tools to identify and monitor potential project threats. Furthermore, you can also create solid risk response strategies.

“When planning a big data project, it is important to separate structured, standardized data that can feed automated data pipelines from unstructured, irregular data that will require significant time and attention to manage,” says Pugsley.

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