One of the best measures of productivity when it comes to data is speed to insight — that is, how quickly employees can begin turning data into meaningful analysis.
Unfortunately, employees often have to spend an inordinate amount of time doing the preliminary work of ETL: extracting data from various sources, transforming it into usable formats and loading it into a data lake or warehouse.
“If it takes me all week to put together a report, is that really a valuable use of my time?” asked Andy MacIsaac, Director of Solutions Marketing for Public Sector at Alteryx, an analytics automation platform.
The Case for Automation
The thing about many of those tedious tasks is that they are perfect candidates for automation, being repetitive and rules-driven. An automation platform can carry out such tasks more quickly, said MacIsaac.
Among other things, an automation platform should:
- Include “connectors” that make it easy to extract data from multiple sources
- Provide drag-and-drop tools for transforming data into new formats
- Automate the process for loading data to its target destination
Automation also reduces the opportunity for human error, MacIsaac said. When tasks are tedious and repetitive, it’s easy for people to slip up, especially if they are trying to knock it out as quickly as possible. Automation tools don’t get bored or distracted and miss stuff or hit the wrong button.
The Case for No-Code/Low-Code
Another way to increase productivity is to provide no-code/low-code tools. Such tools, built around visual and interactive user interfaces, enable people to automate tasks without manually writing code.
With these tools in hand, employees can learn to create their own programs, rather than waiting for someone in the IT department to get around to it. The result? People who are not trained as data specialists can begin delving into analytics and increasing their own data literacy.
The Alteryx Analytics Automation platform provides low-code/no-code tools for the full analytics lifecycle, from doing basic chores like data prep and wrangling to data visualization and enrichment (e.g., adding geospatial data).
The same platform also provides tools for applying artificial intelligence and machine learning, natural language processing and other advanced analytics capabilities.
“We meet people where they are,” MacIsaac said. “Not everybody knows how to code in Python, and that’s perfectly fine. And if they do know Python and want to do some custom coding, they can ingest that into the platform as well.”
In some cases, people who do not start out as data specialists choose to start building their skills, taking advantage of the company’s various training and certification programs, he said. Alteryx also has an engaged user community where people can post questions and share insights.
In any case, the goal is to help people harness the power of data without getting stuck on mundane tasks.
“It’s really about enabling analysts to unleash their creativity, their problem-solving and to really apply themselves to deeper, more valuable work,” MacIsaac said.
This article appears in our guide, “The 5 Habits of Highly Productive Agencies.” To learn more about making your organization more productive, download it here:
