In a perfect world, businesses use data to make strategic business decisions for operations management, customer insights, growth strategies and performance tracking. But not all organizations have figured out how to establish efficient data prep and analytics processes.
To draw valuable analytical insights that benefit the business, organizations must first prep data for analysis. Once prepared, data can be processed and combined with other data sets for business users to analyze.
However, as data sources grow larger and more diverse, the volume of data created on digital information platforms is exploding. As a result, preparing the massive amounts of data flowing into the company every day for analysis is creating significant challenges for organizations looking to turn data into insights.
To realize the full potential of data, everyone must understand the different aspects of data prep and analytics.
With so much data available, preparing data for analytics often falls on both business users and IT resources.
Business users are the main consumers of enterprise data, and may need IT help to understand data, where it is stored and how to access and use the complete set of data required for analytics and reporting.
IT resources that may provide access to the data often don’t fully understand the business use or meaning of the data. The art of transforming, relating and mapping the data to reveal business value is different than the science of granting access.
Instead of just one track organizations need efficient data prep processes involving both, the lines of business and IT department.
To enhance this process, organizations need the support of agile, self-service tools that are easy for business users to use. By employing modern tools and technologies, companies empower business users to quickly prep their own data for analytics and reap the benefits of timely information, without support from the IT department.
Modern technologies are essential in expediting data prep and analytics for business users. By selecting the appropriate tools, organizations can break down data silos and empower business users to quickly prep data for immediate analytical insights, even in a remote work environment.
Today, the solutions that facilitate data prep and analytics by business users feature specific components. For example, a flexible data flow that doesn’t require an underlying data model. This type of flexibility empowers business users to build analytical models without the costs associated with merging different data sources.
Successful analytics projects also require business users to acquire and blend data from virtually any source. They also have to arrange that data and build analytical models. Rapid prototyping capabilities makes it easier for business users to streamline data processes, study new data sources, effectively search for data and make new business discoveries.
Additionally, visualization features and simple query interfaces establish data process consistency by visually documenting each process. And the ability to analyze multiple data sets at the same time.
Features for data quality are also essential to check for reasonability, timeliness, balancing, reconciliation and support business user confidence. When users know they can trust their data, they are motivated to analyze complex data sets and interpret powerful intelligence.
With the right approach to data prep and analytics, business users can confidently predict future outcomes and make informed decisions. When organizations incorporate self-service analytic technologies, they empower business users to quickly prep data. As a result, businesses enable agile analytics to discover new business opportunities and increased efficiency across the organization.
Are you looking for more information about data prep and self-service analytics? Download our white paper, Advancing Self-Service Analytics.
For additional resources on data prep and analytics, read searchbusinessanalytics.techtarget.com’s data preparation definition.