Data is a vital business asset that produces value only if it’s accurate and trustworthy.
Managing data quality has never been so important, as big data continues to push its way into mainstream business. When data quality is suspect, business decisions can be based on false assumptions and inaccurate information. Business users become wary of using the data to make business decisions, and data utilization decreases. Both underutilization of data assets or use of information that isn’t credible prevent compelling analytical insights, and can create customer satisfaction issues. According to a survey from Forrester Consulting, “60 percent of global decision-makers surveyed said they are not very confident in their organization’s data and analytics insights.”
As vendors continue to introduce solutions and tools to help improve data quality, organizations collecting an enormous amount of data across departments in disparate systems, or silos, continue to struggle with data quality. Add to this challenge a thinly-stretched IT team and you quickly realize pulling quality data seems as difficult as finding Big Foot. With no guarantees that IT can get information and insights in time, data quality issues may fall through the cracks and go unresolved, leaving data quality gaps and putting the company at risk.
Fortunately, technology is always advancing. With improvements to self-service visual data preparation tools, business users can quickly access and ready data sets for data quality checks prior to analysis, the first step towards developing the insights they need. This removes business users’ reliance on IT resources, closing the data quality gap and preventing data mishaps that could impact the customer, revenue, or the company’s reputation.
Visual data preparation means that you can see data at every step as you prepare data for analysis. What’s great about visual data preparation is that it does not require any help from the IT department. Using simple drag-and-drop features with both pre-defined and customizable rules, business users can quickly prepare data for analysis by applying or creating a wide variety of these rules without having to write any code. Some of those pre-defined rules include:
Data preparation, while not necessarily that time consuming for IT, often ends up on the back burner, and can take months for business users to get results. By that point, the analysis may not even be timely. Visual data preparation empowers business users, speeds time to analysis, and can help improve data quality.
Visual data preparation improves data quality in two critical ways – speed and agility. Usually prepping data for business users to analyze and draw insights requires the IT department to write code to execute data quality rules. Without data preparation such as in the splitting and parsing example mentioned above, data won’t be matched and data quality will suffer. But visual data preparation enables data quality rules, eliminating long IT wait times and automating quality checks. Business users gain quick and easy access to reliable, accurate data and insights for decision-making.
Additionally, visual data preparation is a self-service function. Any business user can quickly and easily execute rules to improve data quality and prepare data for analysis. Business users are no longer forced to sit idle while they wait for the IT department to validate their data. All the data preparation can be cataloged in a data governance tool, allowing any user to go back and ensure that their data has been appropriately prepared. So next time the boss asks for a financial report or insights on a new strategy, the information needed can be quickly located, prepared and analyzed without any help from IT.
To learn more about visual data preparation, download our data sheet below.
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