Organizations are generating and collecting huge amount of data on a daily basis. These data sets are generated from numerous sources including website clickstream, sensor logs, Point of sales points etc. Analyzing these datasets can reveal insights that can improve business and operations by great lengths. However, most organizations are analyzing less than 20% of their data. Why? – Challenges with data preparation – Users are still following the conventional data preparation processes which were not designed to work with newer data types and data volumes.
Data Preparation – The Traditional Way
Data Preparation process is tedious, time-consuming and messy. Business users often find it hard to handle it themselves. They end up offloading data preparation to IT teams and data analyst who build technology centric solutions ranging from SQL scripts to complex ETL jobs. Due to the complexity involved, these implementations typically run into weeks to months of execution and result in significant cost and time delay.
With the huge demand for data analysts to help with data preparation and analysis, it is also hard for organizations to find the right talent for the job. Moreover, the data cleaning process is very rigid and not agile enough for an analyst to handle requests of adding newer datasets or making modifications to the existing ones.
The Data Preparation Tool of the Future –
Self Service Data Preparation
Modern data analytics and cloud data preparation tools empower users to quickly prepare data for analysis allowing them to spend more time on analyzing data and less time in preparing it. With a self service data preparation interface, businesses can bridge the missing gap between data analysts and business users by giving them full control and insight into the data preparation methodology. Moreover, with empowered business users, who can perform self service data cleaning, enrichment and data discovery, IT teams can now focus on IT centric processes.
In the current big data landscape, with organizations building data lakes using modern data storage, self service data preparation and analytics tools are playing a pivotal role. Organizations can now prepare data for analysis at scale from data lakes. With an ability to work with semi-structured and unstructured data, users can now analyze data which much ease. They can easily connect and blend data from a number of data sources and data types.
Modern data preparation and analytics tools have changed the way businesses have been dealing with data problems. With an ability to perform visual data preparation and analytics, users can now gain instant insights into their data which empowers them to make faster and better decisions.
Self-service data preparation tools are rapidly being recognized as a necessary element to every data discovery or advanced analytics implementation. At Ideata Analytics, we’ve been delivering this service capability to prepare and enrich data yourself – allowing users to spend less time in mundane task of cleaning and enrichment, and more time on analysis. Now you no longer have to rely on IT teams for data preparation activities: