Self-Service Tools Empower Data Users – by Aliyah Wooten, (MSBA Student) William & Mary and Monica Chiarini Tremblay, Ph.D.

Let’s face it, the goal of every business is to make better business decisions than their competitors. But gut instinct, or experience, is no longer enough to remain competitive. Most organizations realize that data should inform an organization’s decisions. The abundance of data, coupled with the availability of cheaper analytic tools, is changing the nature of competition and what we know about business operations. It’s no coincidence that the five most valuable firms in the world — Amazon, Apple, Facebook, Microsoft, Alphabet, the parent company of Google, are also data gatherers (or data distilleries) that exploit data from sales and customer interactions. Together they hold vast sway over customer data.  Investors value these companies at $3.5 trillion.

So, whoever gets the most data, wins? While that’s not necessarily true, having easy access to a broad scope of data can give businesses a competitive edge. Everyone in your organization should have access to use data to inform their decisions. This is why it is important that data be democratized – non-specialists should be able to gather and analyze data without requiring help from IT.

But what happens when an analyst tries to obtain a solution and is met with multiple file types, with different formats and a bunch of missing values? On average, an analysts will spend 80% of their time addressing data preparation issues such as standardization and cleaning. The remaining 20% is dedicated to value added analytics; work that actually answers business questions. Data preparation is a bottleneck or perhaps even a road block for a non-specialist.

Self-service data cleansing tools to the rescue! Self-service tools empower data users with limited experience (non-technical user) to quickly and easily blend data and spend their time conducting analysis instead. Self-service tools have interactive and intuitive interfaces that are designed to be user friendly. The users can cleanse the data without having to write any code – they simply drag and drop color coded operators. Users no longer have to worry about incompatible data as multi-structured files (i.e. CSV, JSON, Excel, SQL). Different data formats  can be easily recognized and imported into the tool. Operators guide the user on filling missing values, identifying and correcting data quality problems. The interfaces guide the users in blending data from multiple sources. Some tools even offer embedded machine learning algorithms that study the data and offer recommendations on how to analyze the trends.

So what tools should you consider? Forrester’s Wave on Data Preparation reports that the following self-service software are leading in the industry: Trifacta, Paxata, Alteryx, Tableau Prep and Datawatch.