What is data harmonization?
Data harmonization is about standardizing & integrating data from different fields, formats, and dimensions. Learn more about its process & best practices.
Having access to clean, high-quality data allows you to analyze sales, marketing efforts, and other factors that contribute to your company’s success.
The data harmonization process:
- Delivers data in the way that you analyze it internally (internal language), as well as the way outside vendors and partners need it (external language)
- Creates hierarchies that allow for big-picture views, and ensures that hierarchies are consistent across data sources
- Provides enough granularity to make decisions, but not so much detail that it’s difficult to sort through the data
- Data harmonization utilizes master data to align data within sources (e.g. standardizing product names within a sales database) as well as across sources (e.g. reconciling social media data that may report weekly data as Sunday-Saturday, vs. retail channel data that may report weekly sales as Monday-Sunday).
How Does Data Harmonization Benefit Businesses?
In simple terms, data harmonization increases the value and utilization of data. Data harmonization also makes it possible for organizations to transform fragmented and inaccurate data into workable information—creating new analyses, insights, and visualizations. This means that data harmonization helps the user reduce the time taken to access business intelligence, discover key insights, and detect early disruptions. It also significantly lowers the overall cost of complex data analysis and the cost of handling data in the long run. If an organization is spending less time scrambling to find the right source of data, then it can spend that time more effectively elsewhere, such as in growing the business and making a significant revenue impact.
Whether an organization has been around for several decades or is a recent start-up, it will inevitably gather a plethora of data. Along with it, there is the distinct possibility that the enormous array of information gathered from a wide variety of sources will have errors and misinformation. Besides this, the sheer volume of information collected over a company's lifespan can be unwieldy and overwhelming.
With data harmonization tools, this data can be a valuable mine of insights and business intelligence. Organizations can learn things about their customers, changing market forces, and even insights about competitors. The good news is that every company across the globe is mining and storing data to make smart business decisions and manage their customers. But first, to make sense of all that data, organizations need to harmonize it.
Most companies spend huge amounts of time and resources on commissioning surveys, conducting focus group sessions, and gathering information from the internet, news channels, and social media networks. All this information does not come together in one manageable, cohesive body but rather as a mish-mash of raw data. To make sense of it as a whole, it needs to be harmonized. Raw, unharmonized data isn’t suitable for business analysis. It often contains irrelevant pointers, misleading values, and duplicate statistics. However, when organizations use data harmonization techniques, they can standardize data and create a single source of verifiable information.
At its simplest, data harmonization enhances the quality and utility of business data. However, data harmonization also makes it possible for business users to transform data and create new data analyses and visualizations without IT involvement. Thus, data harmonization significantly decreases the time to create and access business intelligence insights, while also lowering the total cost of data analysis.
Who uses data harmonization?
Data harmonization technology is applicable in a variety of business functions, particularly sales and marketing. As a relatively new approach to data analysis and visualization, data harmonization is not yet widely used or understood.
Best practices in harmonization
Harmonization is typically a mix of automated steps (often using artificial intelligence) and manual efforts, with leading vendors automating 60 percent or more of the process. The goal is to use artificial intelligence as much as possible in order to reduce errors and shorten the time to insight.
- Create data models that meet future plans as well as immediate needs
- Offer deep industry and category expertise, which saves you time
- Provide a no-code environment that lets data analysts harmonize the data directly
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