Simplify and Improve Analytics with Self-Serve Data Prep |
Posted: February 1, 2024 |
Data Scientists spend a lot of time gathering and preparing data for analysis, and that is time they could spend more productively performing tasks that add value and strategic direction. Business users cannot even hope to prepare data for analytics – at least not without the right tools.
Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation? It’s simple. Because, without the right preparation, analytics can produce incomplete, incorrect results, thereby sending the business off in the wrong direction and resulting in a loss of confidence in analytics for decision-making.
‘Self-Serve Data Preparation can benefit your business users and help to transform them into Citizen Data Scientists.’
When an enterprise chooses the right self-serve data preparation tools, it can confidently use these tools to prepare for and execute analytics that will result in concise, clear results that benefit the organization, its users and its customers and stakeholders.
Self-Service Data Prep empowers every business user and allows them to prepare data for their analytics using tools that enable data extraction transformation and loading – ETL for business users! In other words, business users can quickly move data into the analytics system without waiting for IT.
The right self-serve data prep solution can provide easy-to-use yet sophisticated data prep tools that are suitable for your business users, and enable data preparation techniques like:
Users can:
‘Self-Service Data Prep empowers every business user and allows them to prepare data for their analytics using tools that enable data extraction transformation and loading.’
Find out how Self-Serve Data Preparation can benefit your business users and help to transform them into Citizen Data Scientists, and how it can provide an advantage to your data scientists, business analysts and IT team members.
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