Dan Woods is CTO and founder of CITO Research. He has written more than 20 books about the strategic intersection of business and technology. Dan writes about data science, cloud computing, mobility, and IT management in articles, books, and blogs, as well as in his popular column on Forbes.com. This is the fourth and final segment of his Signal Hunters series. To catch up on the other three parts, check out Why You Should Empower Analysts to Wrangle Their Own Data, What is Signal Hunting? An Explanation for Business Analysts, and How Business Analysts Can Become Better Signal Hunters.
There’s no doubt that the volumes of data companies collect hold valuable business insights. But those insights don’t necessarily surface in the day-to-day grunt work that comes from generating reports. Insights must be sought out – hunted down, even – by domain experts who understand the data. In other words, business analysts must become signal hunters. They must explore and interact with the data for the purpose of discovery.
When business analysts become signal hunters, innovation takes place. Domain experts are empowered to explore parts of the business they haven’t been able to before and uncover interesting insights that lead to big value gains for the company. The challenge comes from finding the time to go signal hunting. But it’s not impossible. Here are four ways to find the time you need to go signal hunting.
1) Avoid doing the same work over and over again.
You can’t rely on a machine to make important decisions about what data is worth keeping or what structure to induce. Those decisions can really only be made by a domain expert. That said, domain experts can be empowered to do the work of data wrangling more efficiently and effectively. That’s what Trifacta does. It generates the command that performs data transformation. The business analyst runs it on a sample and if the command runs as expected, they can then run it on the entire dataset.
2) Use a tool that lets you do big data wrangling without big data skills.
Domain experts often know what they’re trying to get out of data and the analytics they’re trying to perform, but they need IT’s help to wrangle data – that is, structure, clean, enrich, validate and publish the data for analysis. In the world of big data, domain experts must be empowered to do their own data wrangling. That means interacting directly with data, making changes to schemas and cleansing the data themselves. Trifacta enables domain experts to do just that, even going so far as to suggest operations that the user can perform to clean data.
3) Reduce data prep time.
Preparing data is the most time-consuming analytics task. In fact, business analysts spend 80% of their time wrangling data and only 20% of their time analyzing it. It stands to reason that if you can reduce the amount of time you spend data wrangling, then you can increase the amount of time you have for signal hunting and analysis.
A significant portion of data preparation time is focused on one-off exploratory work, which involves figuring out the right transformations to perform. Trifacta makes it faster to assess whether the transformations you’re doing are correct, thereby decreasing preparation time.
4) Answer others’ questions faster.
Regardless of the type of report you produce, someone inevitably has a follow-on question. In the past, that would require going back to IT and asking for a new cut of the data, adding weeks to the analysis. With Trifacta, performing different aggregations on the data is a fluid follow-up step to the original reporting work. Business analysts can easily pull up a dataset, look at a script, make one or two edits to the script, rerun the data, pull up the results and be done – all in a matter of minutes. There’s even time left over to ask the questions you’ve been wondering about yourself.
5) Work directly with interaction data.
Customer interaction data is typically semi-structured, and it holds the key to understanding customers. Whether it comes from apps, social media, web logs, or other sources, interaction data is critical qualitative information. Business analysts from marketing (among other disciplines) must be able to work with this data directly because they are the ones who understand the context of that data and can extract its meaning. What items did the customer view before purchasing? Did the customer look at reviews? Does that tweet express delight or was it sarcastic? With Trifacta, business analysts are empowered to work with this type of data directly and effectively, ensuring it can be analyzed by those who best understand a given market or segment.
Trifacta enables domain experts to efficiently wrangle and understand their own data, helping them find signals and – ultimately – innovate with data.
To learn more about our Trifacta Success Stories, check out the customer testimonial video we shot with the Royal Bank of Scotland. Featuring Head of Data Science and Customer Decisioning Jessica Cuthbertson, the video covers how Trifacta helps RBS improve customer service.