Why Use Data Preparation Tools – tutorial transcript
The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers .
The sheer volume of data combined with its high level of complexity, have made it challenging if not impossible to continue to rely on traditional data preparation tools, such as Excel spreadsheets, to make decisions.
These traditional approaches overload the data analyst with repetitive and time-consuming data preparation tasks, that require countless database queries, and gathering of data from multiple online data sources, such as Google Analytics.
Instead, increasing interest in methods of gathering and preparing data has created a shift from total reliance on IT staff, to self-serve data preparation.
At the same time, the broad availability of data from various sources, and with varying degrees of quality and consistency, has given a rise to new data preparation principles and techniques, with the ultimate goal of improving the speed of the data preparation workflows, and consequently, to establish better support for data-driven decision making.
Data preparation is a key process in the business intelligence and data warehousing arena – and it’s all about automating data movement and building repeatable, robust processes that take raw data, clean it, fix it, enrich it, and then load it into a location where it can be easily queried and analyzed.
You can download a free trial of Analytics Canvas to follow along with the video.