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Use Cases to Help Your Team Explore the Potential of Data Science

Data science has applications across all departments of business, making it one of the most crucial professional skills to develop today.

What is data science?

Data science is a broad, multidisciplinary field that focuses on organizing, understanding, and utilizing data in practical ways.

In business, data science usually involves the collection, organization, and analysis of business data into specific forms meant to help decision makers understand information pertinent to the business decisions at hand. Based on the decision, this data may include sales figures, marketing performance data, employee productivity, or otherwise.

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Why use data science?

The applications of data science in business are practically endless. Data can be used to inform decision-making across sales, marketing, finance, hiring, and beyond.

Perhaps most importantly, as businesses continue to collect data, data science will only become more valuable over time. The more accurately, quickly, and effectively your business can parse and use its data to make informed decisions, the greater a competitive edge you can gain from the data.

Data science use cases

These are just a few of the various practical data science use cases in modern business, along with LinkedIn Learning resources to empower your team.

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Data visualization and data-powered storytelling

One of the key basic applications of data science is in data visualization. Data scientists can parse, organize, and collect data into visual presentations that help all business departments understand and analyze performance patterns.

These visualizations are key for understanding and presenting the narrative behind your business’s data. For example, by using data science to present a visualized report on the year-over-year growth of a particular initiative or department, you could make a data-informed argument on the effectiveness of that initiative to stakeholders.

Building custom database applications and machine learning

Data scientists can use various development tools to build customized applications within their business’s database. These applications allow them to automate key data-related tasks, such as cleaning, preprocessing, and gathering data for regular reports. Advanced machine learning models can even adapt and evolve to provide more useful analyses over time.

Sales analysis and forecasting

Data science has a huge number of applications for sales analysis and forecasting. Data scientists can visualize sales data while identifying trends and patterns. These skills are also useful for analyzing the sales funnel and customer journey to find key strengths and weaknesses in the process, surfacing unseen opportunities.

Data science is fundamental to many modern sales forecasting methodologies. Data scientists use various techniques in forecasting, such as a time series analysis, which analyzes your business’s historical sales data, identifying trends, seasonality, and patterns among your customer segments.

Customer identification and segmentation

By analyzing data from your sales and marketing teams, data scientists can identify key customer segments interested in your products and services. This analysis lays groundwork for data-informed decisions on marketing and sales targeting, by creating material designed to appeal to the needs and interests of the segments discovered via your data.

Financial planning and forecasting

Data science can be applied by your financial department and C-suite to visualize and analyze financial health over time. This leads to smart and proactive decision-making for the business.

Explore many more hands-on data science use cases

The applications of data science are so various that these practical use cases barely scratch the surface. If you’d like to learn much more about how your team could use data science to improve your business, check out the learning path on Hands-On Data Science for examples and expert-led courses on how to get started.

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