The Right Self-Serve Data Preparation Solution is Sophisticated, Easy-to-Use and Ensures User Adoption!

When your enterprise decides to roll out analytics for business users, it is important to implement the right solution. If your team has easy-to-use tools and features, you are much more likely to experience the user adoption you want and to improve data literacy and data democratization across the organization.

Gartner predicts that, ‘data preparation will become a critical capability in more than 60% of data integration, analytics/BI, data science, data engineering and data lake enablement platforms.’

If you want to optimize your analytical results, be sure that the augmented analytics solution you choose has seamless, self-serve data preparation capability.

‘As you consider augmented analytics solutions, be sure to thoroughly review the features and functionality for data preparation.’

In this article, we look at the features and capabilities of a comprehensive self-serve data prep solution.

Support for Business Users – Be sure that the self-serve data preparation solution you choose is easy enough for business users with average technical skills. Look for a solution with no requirement for SQL skills or the need for manual skills in data extraction, transformation, and loading (ETL). An augmented analytics solution that leverages machine learning can provide recommendations for users, so that they achieve the results they need, quickly and easily.

Sophisticated Functionality – Don’t sacrifice functionality to get ease-of-use. As your users become accustomed to augmented analytics, they will want the ability to quickly, and easily, gather data, integrated from disparate data sources. Users can then prepare that data – transforming, shaping, reducing, combining, exploring, cleaning, sampling, and aggregating data, to get the dataset users wish to analyze. Machine learning capability determines the best techniques, and the best fit transformations for data so that the outcome is clear and concise. Features and functionality should include sampling, outliers, the ability to easily connect and mash-up data, the tools to explore, clean, shape, reduce and combine data, data searching, profiling, and cataloging, auto suggestions for relationships, JOINS and type casts, data insight and data quality index, and data lineage and collaboration, social BI enabling and data popularity features, as well as comprehensive data governance tools.

For more information on self-serve data preparation and real examples of easy-to-use tools for your team, explore these videos:

These business use cases illustrate the sophisticated functionality and ease-of-use of a robust Self-Serve Data Preparation solution.

‘If you want to optimize your analytical results, be sure that the augmented analytics solution you choose has seamless, self-serve data preparation capability.’

As you consider augmented analytics solutions, be sure to thoroughly review the features and functionality for data preparation. With the right solution, your users will want to adopt and leverage analytics and you will enjoy improved data literacy, data democratization and user adoption. Find out how Self-Serve Data Preparation can help your enterprise to roll-out augmented analytics and ensure user adoption with tools that are flexible enough to respond to every user need. For more information about the benefits of self-serve data prep, see our blog: ‘Self-Serve Data Preparation Improves Results.’

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