Read time: 4 mins
Discover the Business Value of Data Analysis
Data analysts play a key role in helping business leaders make informed choices. By collecting, storing, and analysing data, a data analyst can help distinguish between effective and ineffective practices, identify cost-cutting measures, and recommend solutions to key problems.
Find out more about the part data analysts play in today’s business environment with Şebnem Er, Convenor on the University of Cape Town Business Analytics online short course.
Transcript
With the start of the Fourth Industrial Revolution, businesses are presented with a significant problem: how do they appropriately collect, store, and analyse the large volumes of data that are retrieved from multiple departments in the company? Technological advances have made it much easier for data collection to occur. And this advancement is set to continue for the foreseeable future. This has led to an increased need for data analysts.
The key function of a data analyst is to extract relevant insights from data to inform business decisions. Data analysts should have analytical and reporting capabilities, be able to monitor quality and performance within an organisation, and offer solutions for improvement.
Some key functions of a data analyst include: collecting high-quality data, conducting statistical analysis on data, interpreting the results of these analyses, collating the results, creating reports based on the results, and finally presenting insights to relevant stakeholders.
Jane is a data analyst that has recently been hired by a large apparel company. Until now, the company has had little experience in data analytics, and Jane was hired to fill this gap. Jane’s initial steps are to establish an understanding of what business decisions the company’s trying to answer and what problems they are trying to solve.
After meeting with the company’s board of directors, she is told that the business is primarily interested in streamlining their supply chain and effectively scaling up clothing production. With this information, Jane moves on to identify the available data and data sources. This includes whether the data is numerical in nature, such as resource pricing and employee compensation, or whether it is non-numeric, such as demographics and education status.
She quickly realises that there’s no central database for locating the company’s data, but that each department collects and stores their own. Now that Jane has an understanding of how the company handles data, she defines robust data collection procedures that establish clear guidelines for how information from the company’s different branches are to be collected.
Jane is also working to establish a central database for all the company’s information. Once Jane has an understanding of the data pipeline and what types of data are available, she returns to the problem that the company is trying to solve. Based on her discussion with the company’s board and the data available to her, she chooses the appropriate types of statistical analysis she can perform on various datasets.
She then collates this data into digestible, informative pieces and presents her findings to the board, using data visualisation tools. Jane made sure to understand the types of data available to her and the sources that this data came from.
After performing the analysis, she created information reports and presented the results to the company board, who were then able to make data-driven decisions for the company’s future.