Data analytics are critical to business intelligence, providing companies with valuable insights that can be applied to improve everything from product offerings to targeted advertising, from streamlining processes to expanding operations.
The insight generated by data analytics can be used to improve data-driven decision making, by providing better data on which to base these decisions – data that is more timely, more reliable, and above all, more accurate.
This is the primary benefit of deterministic data: it is based on real-world behaviors. Probabilistic data, on the other hand, is inferred by a consumer’s association with a group with common characteristics or behaviors.
What is Deterministic Data?
Deterministic data is considered to be factual: it is based on real-world, first-person attributes, and is accurate and verifiable. When used to define a business practice, drive decision-making, or group customers into an audience, deterministic data is specific and behavior-based.
Other types of analytics take some deterministic factors, but seek to fill a gap in knowledge with the most likely, or probable additional characteristics or outcomes. While probabilistic analytics are data-driven, the quality and accuracy of the data is less than with deterministic data. This has a direct relationship to the quality and accuracy of the decisions that are made using that data.
Tips to Conduct a Deterministic Data Analysis
1. Ensure that the Data is Verified and Accurate
To ensure that data is verified and accurate, it is important to understand data sources, scale and methodology; to know that data is fresh, and to understand what type of data you are reviewing: deterministic or probabilistic.
2. Complete Data Cleansing
Before data analytics can be implemented, it is critical to ensure that data is clean. This means detecting, correcting, or eliminating and false, erroneous, corrupt, or duplicate records in a data set. Data cleansing requires an investment of time and resources, so if data is purchased from a third-party provider, it is important to verify their data cleansing standards to ensure that data is usable upon receipt.
3. Create a Strategy
Be specific about what you are hoping to learn. Are you using analytics to identify a new audience for your products or to improve audience targeting? Know what you are looking for, and ensure that you have clean, consistent, accurate data that will provide the insight you need.
4. Keep Your Data Fresh
Ensuring that data is updated regularly and comparing results over time will help you identify trends and changes, as well as confirm the accuracy of insights gained from analytics. If your audience interests change over time, targeted marketing will no longer be effective unless data is updated accordingly. Advertisers, like all business owners, need the freshest data to make the best decisions.
Data analytics are extremely useful for businesses, providing insights that can help achieve strategic goals: identifying new opportunities, improving marketing ROI, reducing overhead and more. However, in order to conduct a useful deterministic data analysis, it is important that you understand the type of data that you are using, and ensure that it is clean, comprehensive and accurate before analytics are applied.
