What is data transformation, and why does it matter?

Data flow illustration showing glowing blue, pink, and yellow lines becoming integrated binary.If there’s one thing you can count on in life, it’s the need to continually transform. Only those who adapt will survive and succeed. As Benjamin Franklin once said, “When you are finished changing, you’re finished.”

Adaptation is a necessity not only for individuals and businesses but also for data. If you want to realize the full potential of your informational assets, data transformation is essential. Here’s everything you should know about the process and how it lays the foundation for success in various professional pursuits, including the development of artificial intelligence models.

What is data transformation?

You’ve likely heard the quote, “Knowledge is power,” attributed to Francis Bacon and invoked multiple times by Thomas Jefferson in his correspondence, according to the Thomas Jefferson Foundation. By extension, the wealth of data available to most modern businesses has the potential to be extremely powerful. However, to successfully harness the power of that data, you must first optimize it, according to Hewlett Packard Enterprise (HPE).

Data transformation is the process of converting, structuring, cleaning and enriching data to prepare it for reporting, analysis, storage, and training machine learning or AI models, HPE explains. Refining raw data is imperative for businesses that want to realize its full value and drive innovation and efficiency.

How to transform data

The details of data transformation depend on the specifics of the project, according to IBM. It could be as simple as standardizing the format of dates in a spreadsheet or as complicated as consolidating input from numerous sources into a single consistent dataset. Depending on the circumstances, the process might require the oversight of individuals with high-level data science and data engineering skills.

There are various ways to approach data transformation. Organizations with on-premises data warehouses commonly employ an extract, transform, load (ETL) methodology, according to Spiceworks. Alternatively, you can opt for an extract, load, transform (ETL) strategy in which you load raw data into a warehouse and convert it after receiving queries.

Data scientists can employ a range of techniques to optimize data during the transformation process, according to IBM. Depending on the project, they might rely on one or more of these procedures.

  • Cleaning, or enhancing quality by correcting errors and inconsistencies
  • Normalization, or standardizing values in one format
  • Imputation, or filling in missing information with estimated values
  • Aggregation, or combining multiple datasets into one
  • Encoding, or converting categorical data to numerical form
  • Enrichment, or supplementing data with information from external sources
  • Splitting, or creating subsets for separate purposes
  • Generalization, or abstracting data and creating a summary that’s easier to digest
  • Visualization, or converting the data to graphics
  • Discretization, or sorting data into separate buckets or intervals

Why data transformation matters

To stand out in today’s increasingly digital world, businesses must effectively process and capitalize on large amounts of data, according to IBM. Once you’ve optimized your data, you can utilize it for various purposes, including the following.

  • Training machine learning/AI models, which require clean data to avoid functional issues and biases
  • Conducting analysis for business intelligence to create reports and dashboards
  • Migrating from on-premises systems to cloud solutions
  • Storing data for querying and analysis in a data lake or warehouse

Data transformation comes with many potential advantages. Here are some notable benefits, according to HPE.

  • Increased data consistency
  • Improved accuracy and understanding due to fixing errors and filling in missing information
  • Enhanced algorithm and machine learning model performance
  • Improved ability to gain insights and identify trends
  • Ability to view the big picture by consolidating multiple datasets from various sources

Ultimately, refining and optimizing your data allows you to turn potential into actual power. Through data transformation, you can translate muddled information into clear insights that drive innovation.

Our trusted technology advisors can help you craft a data strategy and explore IT solutions that align with your business needs. With over 20 years of IT experience, partnerships with leading suppliers, the latest market data, and a tool that rapidly generates comparison matrices, we can efficiently identify the best technology offerings for your organization and save you dozens of hours you’d otherwise spend navigating complex marketplaces on your own.

Start by calling 877-599-3999 or emailing sales@stratospherenetworks.com.

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