Why Data Prep is Critical to Analytics Success

    Business Strategy & Perspectives

There is an explosion of data being created in the world today and it’s no secret that the organizations who are able to drive value and innovation from this data will succeed. However, companies large and small struggle to analyze and make use of the complexity and scale of today’s data. In fact, the process of converting raw data into a format that is usable for analysis takes up to 80% of any analysis process.

Data preparation is where people spend the most time in an analytics problem. It is where things get bogged down. And sometimes it is where analysts end up giving up on their analysis, not because the analysis isn’t interesting, but because the process of preparing data is too slow and cumbersome. As many organizations already know, this problem is not limited to interesting experiments but can be found across almost any business looking to leverage data to inform decisions or drive new sources of revenue.

Despite the plethora of advancements in analytics technology over the past few years, data still needs to be in a coherent format and structured to be analyzed. The structure of choice is typically the row and column format found in Excel spreadsheets or relational databases. Yet, when thinking about the world’s data, not much of it is in a structure or format that is ready to be analyzed in Excel. On top of that, even data stored in native formats in new technologies like Hadoop need to be joined at some point with data from more structured relational sources for further insights. This is where the process becomes incredibly important for transforming raw, dirty data into usable information.

We show you how to transform your data in our webinar with our guests from Trifacta: Fuel Analytics with with Self-Service Hadoop Data Prep.  Trifacta enables organizations to access and analyze more data, faster by making the data wrangling process intuitive and efficient.