Today’s businesses of all sizes, and in all sectors and industries, have the ability to collect, store, process and transmit massive amounts of data. In our modern data-driven marketplace, the vital role of digital information is to empower business leaders like you in your decision-making efforts.

By strategically sifting through the heavy noise ratio of your unchecked tomes of data to mine the facts, trends and statistical numbers embedded in your data, you suddenly become armed with the right information to make the best decisions for your business, in terms of strategy, growth and more.

Data analytics is important to every department in your organization

Every department in your organization needs specific data to help make the best decisions for their operational needs and goals for productivity and profit. Every corridor of your operations, from specialized areas like human resources and marketing to your overarching executive team, relies on data in its most useful state, once having undergone analytics.

The key to successful data analytics starts with a solid strategy

No matter what your focus is for your next data analysis, it is important to develop a strong data analytics strategy. You don’t want to end up with yet another pile of random information. You want the right information, which means coming up with a general idea of the insights you want to gain from your data analytics that will help improve your company’s decision-making process.

Here is a set of considerations to help you develop your organization’s specialized data analytics strategy:

  • Select desired outcomes by determining your pain points. In order to turn your data into hard-driving decision-making tools, you need to start your search for insights before you begin the data gathering process. Prepare a set of questions focused on your organization’s strategy, budget, goals, department and clients that will help you ultimately reach relevant insights. Basically, begin with the end in mind.
  • Determine the time, talent and internal resources needed for a solid data analysis. Do you have a data analyst on your team? These professionals are trained in statistical analysis and data modeling. Whether you have a data analyst on staff or work with an auditing firm with highly skilled data analysts, this person is pivotal in keeping data organized and actionable and for identifying and interpreting data analytics. Additionally, do you have the necessary internal resources such as the necessary software? Some firms decide on the need for a data analyst and other internal resources based on their budget and perceived need for data analytics.
  • Do you have the necessary tools to perform high-caliber data analytics? Tools needed to perform data analytics includes those for data extraction, data aggregation, data filtering, data cleaning, data analysis, data visualization and modeling, and data reporting.

The core tasks in performing data analytics

Once you have set your objectives and determined your resource needs, performing your own data analytics comes down to following key elements:

  • Data aggregation. Data aggregation is where you pull together multiple and varied sources of data together into one common format and place (sometimes referred to as a data lake or data warehouse), which will enable you to perform smarter analytics on combined data than any one system’s canned reporting could have produced on its own previously.
  • Data visualization. Data visualization offers a graphical, easy-to-read representation of your collected data. A good solution allows you to drill down into the detail for focused analysis in real-time.
  • Process automation. Using automation tools, such as macros and scripting in Excel or even bots (RPA = Robotic Process Automation), you can streamline the mundane, repeatable tasks that are often performed over and over every day, week or month. What was previously a lengthy task at month-end could be replaced by the click of a button and review of the results and exceptions.

Common uses for data analytics

Today’s business leaders and data experts are finding an ever-increasing number of uses for data analytics that include the following:

  • Marketing to targeted audiences
  • Understand customer base to improve customer engagement and retention
  • Improve logistics and operations
  • Financial fraud prevention and detection
  • Fraud forensics analysis
  • Data waste reduction and cleanup (vendor master file, etc.)
  • Evaluate employee performance criteria to help improve engagement and productivity
  • Evaluation of training methodologies and effectiveness
  • Uncover cyber threats through data monitoring
  • Internal control and policy monitoring

Data analytics is an essential tool in understanding your organization and its needs for growth and success for now and the future.

If you need to bounce some ideas off someone or need to talk through a problem or potential solution, consider reaching out to GBQ’s IT Services team, who has experience in implementing data analytics strategies. We would love to take this adventure with you!

GBQ IT Services is one team of builders, breakers, operators, and auditors with access to a consortium of 50 experienced IT, cyber and assurance professionals delivering IT risk, cybersecurity, and productivity solutions.

We build value through IT strategy; protect value with information risk and cybersecurity services; measure value and improve productivity with data analytics and process automation, and assure value through IT audit services.

« Back