Let’s talk about data preparation! That often cumbersome, always complex process by which data scientists and IT professionals gather and prepare data for analysis. Data prep involves the extraction and transformation of raw data to prepare that data for analysis. It includes cleaning and reducing that data by removing outliers and standardizing data formats, among other things. Without data preparation, data analysis can often be misleading and incorrect – garbage in/garbage out, if you will.
Data preparation tools are an important part of this process; a process that is typically managed by data scientists and others who understand how to perform these tasks.
But, that restrictive environment often delays data analysis and causes frustration for those who need the data to make decisions and for those who are swamped with data prep projects and cannot keep up with demand.
What if business users had the tools to perform self-serve data preparation? Self-Service Data Prep provides tools to empower users, so they can prepare data for analytics and perform data extraction transformation and loading. With these tools, business users can quickly move data into the analytics system without waiting for assistance.
With self-serve data preparation, business users can access sophisticated, intuitive tools to compile and prepare data for use in analytics to test hypotheses, visualize data and create and share reports with other users.
This self-serve environment is made possible by machine learning capability that provides guidance to determine the best techniques and the best fit transformations for the data business users want to analyze, allowing for better understanding of data.