Today, companies have access to petabytes of information. Yet, why is it so difficult for data analysts to use this data? It’s a chore to retrieve just a sliver of data from a single database and an even harder task to prepare disparate data for analysis.
One of the most challenging aspects of unifying multiple data sources is when:
- Calculable data is stored as a string, or text field, and
- Text fields are formatted differently across each data source
To enable analysis, you need to be able to extract key elements of data from their string fields and transform them into consistent numeric fields that are calculation-ready; however, text manipulations are usually reserved for (likely overbooked) programmers and data scientists. As a result, data analysts are held back from being able to quickly extract insights needed to drive the business forward.
But what happens when data analysts and other users can easily execute sophisticated, big data text manipulation on their own? Using a rich, easy-to-use library of string manipulation and text analytic functions, they can:
- Conduct a wider range of data preparation & analytics – without reliance on IT
- Perform valuable analysis of data stored in text fields
- Gain new & deeper business insights from big data
Empower data analysts to tackle big data challenges on their own & overcome analytic roadblocks.
Download this guide to learn:
- How to extract valuable information from data stored as a text field
- Techniques for utilizing string functions to harmonize data and enable analysis
- How to easily and intuitively perform string manipulations