Elevate Your Data Science Initiatives with Data Enrichment
In recent years, the field of data science has been advancing in leaps and bounds. In most enterprises, executives are aware that they need to be doing more with both internal data and external data by leveraging advanced analytics. They understand that machine learning and artificial intelligence will be rich sources for competitive advantage in the years ahead. The challenge for many is the question of exactly how to get started.
Many companies have begun to collect their data and ensure that it is stored where it can be put to use at some point in the future. That often includes text data, semi-structured and unstructured data including service tickets, user reviews, and social media posts, as well as more traditional sources like ERP transactional data. Simply by gathering, organizing, and ensuring that this information is preserved in such a way that it can be used later, these businesses are laying the foundation to gain future advantages from data analytics.
Many of them may already be well-positioned to gain significant business value from their existing data. Data enrichment makes that possible. It provides the “low hanging fruit” that produces powerful business insights, which, in turn, can drive immediate value.
According to a 2021 survey by Transforming Data With Intelligence (TWDI), approximately 30% of enterprises are already using external data. Just as many intend to begin using external data sometime within the next year. Trends surrounding geospatial data show a similar pattern. About one-third of companies are using location data in one way or another, and more than 25% of the remaining enterprises responding to the TWDI survey intend to start using geospatial within the next year.
Those trends illustrate a growing awareness that for companies seeking to elicit value from their corporate information, data enrichment provides a natural starting point. In a recent webinar co-sponsored by Precisely, experts from TDWI, Ironside, and Precisely discussed these trends, including how companies can get started leveraging data science more effectively to produce better business results.
What is Data Enrichment?
Fern Halper, TWDI’s Senior Research Director for Advanced Analytics, defines data enrichment as “the process of combining company data with diverse data from other systems or third-party data sources.”
A typical example might involve a company seeking to understand its customers more thoroughly. By combining its existing customer data with external demographic data and behavioral information, the company can gain a much richer, more nuanced understanding of its customers.
A telecommunications provider, for example, might be able to learn more about age, family status, and life events that could impact a subscriber’s decision to cut costs or consider moving to a different provider, or which could potentially indicate an opportunity to upsell the customer to a new product or service.
This type of scenario provides tremendous value, even if your organization is beginning with a relatively small data set. Pam Askar, Ph.D., Director of Advanced Analytics at Ironside Group, provided this analogy: if you give students a stack of books about science, they can potentially learn a lot about that single subject. Instead, if you give them a collection of books about related topics, then suddenly they have the opportunity to connect information in a more meaningful and powerful way. In effect, data enrichment extends the scope and value of your existing corporate data by matching it with high-quality curated data from third-party sources.
The Unique Role of Geospatial Data
Location-based data presents an especially significant opportunity for value creation, simply because it unlocks so much information about where a particular entity exists in time and space, including its physical characteristics, what is nearby, what kind of traffic or weather conditions exist at any given time, and so on. Precisely’s location-based data, for example, can unlock information pertaining to over 9,000 different attributes for any given location in North America. The company manages similar data sets for countries and regions around the world. When combined with an organization’s existing corporate data, it provides extraordinarily rich context and valuable insights.
Geospatial data is especially challenging, though, because it defies many of the standard forms and definitions that you normally think of when it comes to structured data. Precisely’s Director of Location Intelligence Products Mike Ashmore describes the challenges of working with geospatial data by comparing it to the information stored in a spreadsheet. “You can’t put squiggly lines in a spreadsheet,” he often says.
For any given point (such as a street address), location intelligence calls are the calculation of distances, catchment areas based on average driving time, or susceptibility to specific types of extreme weather events or other natural disasters. This type of analysis, and many other examples from within the field of location intelligence, call for specialized tools and capabilities. Nevertheless, location intelligence is worth the investment, simply because it has the potential to generate so much business value in so many different ways.
Getting Started With Data Enrichment
For business leaders seeking to extract business value from their corporate data, it’s important to start with a good business case. That typically involves interviewing multiple stakeholders to understand what types of business outcomes are the highest priorities. That must be overlaid with the organization’s data assets to map out high-value opportunities.
The company might have identified a strong business case for advanced analytics, for example, but if there are serious concerns about the dataset required for that analysis, then the company must first address any data quality or data governance issues. In any case, the process must include a mix of skills, from data scientists to business users and strategic decision-makers. As Ironside’s Pam Askar puts it, “data science is a team sport.”
Precisely provides a full range of capabilities that help enterprises to manage and integrate their data, maintain high data quality, enrich that information with curated external data, and unlock context using geospatial data. Each of those four elements (integration, data quality, enrichment, and location intelligence) provides value, but in combination, they create a platform for data integrity that yields a competitive advantage.
To learn more about data enrichment, including Precisely’s suite of data enrichment and location intelligence products, watch the free on-demand webinar today, Empowering Your Data Science with Data Enrichment, hosted by TWDI and co-sponsored by Precisely.