Exploratory Analysis
We are a strong believer that any insights from your data is only as good as the data itself. We can perform an assessment on your data to provide recommendations on data use; including how your data can be standardised or cleansed based on industry standards and best practice.
What does this involve?
Data matching and validation
Enrich and validate your data assets by linking your data with other internal or external datasets. We have worked extensively with CRM (customer and address data) and can match your addresses against other address APIs to validate and cleanse your address data.
We have worked with clients and partners to conduct customer level matching which is secured and privacy compliant.
Exploratory data analysis (EDA)
The main purpose of performing an EDA is to gain a better understanding of data’s characteristics. This is an important step for data analysts and data scientists to identify any patterns or outliers, test hypotheses, or validate assumptions.
Combining rich data understanding and your knowledge of the business will enable powerful insights and models to be built.
Data Cleaning
This is the first step to building out your company’s data assets. Our data analysts can help you refine, de-duplicate and standardise your data to enable more powerful insights. Add an additional layer of business context to your data by introducing business rules to the data and eliminate dirty or redundant data.
The end outcome is clean and accurate data for consumption for analysis and data scientists.