Today, 3rd-party data is the name of the game. Organizations increasingly must explore, structure, and combine vast amounts of unfamiliar data from multiple sources, such as marketing and sales technology, government data, and data from business partners or clients. A recent Forbes article cites a study in which data scientists estimated that they spend almost 20% of their time just collecting data, taking valuable time away from analysis of said data.
Not only is there a lot of third party data, you probably have little over control over its timing and format. From Excel to CSV to raw text files, to JSON and API calls, the problem is growing in size and scope. As mentioned in the Forbes article above, cleaning and organizing data accounted for a full 60% of an analyst’s time. Altogether, that means that analysts spend about 80% of their workweek collecting, formatting, and cleaning data for analysis.
Where Excel Doesn’t Excel
To ensure you are providing the best insights and making the best recommendations to your clients, you must clean your data to prepare it for analysis. Your reputation and integrity depend on it. Until recently, this required sophisticated manipulation of Excel, made even more difficult by the fact that Excel makes it hard to get a full picture of big data.
For example, Excel has limited features in assessing data quality. Unless you know exactly what type of errors you’re looking for, it’s hard to know if the data is clean. While identifying dupes and nulls is doable, discovering data quality issues such as invalid numbers, incorrect dates, and formatting standards proves time-consuming. Similarly, assessing data inconsistency between spreadsheets or across a workbook becomes a complex, laborious task requiring extensive IF condition formulas and VLOOKUPS to discover errors you believe are there, leaving you blind to those errors you did not think to look for.
After assessing the quality of the data comes the even more difficult task of cleaning the data. It’s a repetitive, voluminous process that Excel was not created to tackle – made even more difficult by the sheer volume of data coming in from one’s own organization as well as 3rd-party participants. To make the data-cleaning process faster so that analysts can focus on analysis, one must iterate the cleaning process—something Excel just doesn’t do well.
Clean Data Like a Boss
Profiling data is automatic with Trifacta’s data wrangling solutions. Every time you open a data set or derive a new value from existing data, Trifacta automatically assesses the data quality to look for valid, mismatched, or missing information, as well as the overall value distribution. As an analyst, you don’t have to do anything; the process is dynamic and automated.
Beyond initial screening, analysts can drill down to get additional signals about the data such as outliers, minimum, median, and standard deviation; and frequent values. This frees you to focus on the data-cleaning rules that must be implemented. Trifacta was built to support this process as well, suggesting transformation rules one should apply to the data to solve the issues.
With extensive visualization tools and specialized functions, Trifacta easily moves into the next step to clean and format data, ensuring its trustworthiness. Through lookup tools and pattern- matching functions, Data Wrangler guarantees data de-duplication, consistency, normalization and standardization.
Your Credibility as an Analyst Depends on Clean 3rd Party Data
As an analyst, you want to be laser-focused on analyzing data to provide actionable insights. To do so, your credibility depends on having the best tools to secure accurate, clean information. Gone are the days of grappling with inefficient tools. With Trifacta, you can automatically and iteratively clean data, allowing you to quickly explore, structure, and integrate 3rd party data with your own.
Eliminating reliance on manual data preparation can help you and your organization get faster and more accurate business analysis and better business results. Trifacta helps you have more confidence in your data, which means you can finally harness the power of big data to transform the future of your business.