Data and analytics are no longer nice to have for businesses; it is essential. The available amount of data is overwhelming, and the tools to help make sense of it are more sophisticated than ever before.

As new technologies emerge and disrupt the status quo, businesses must adapt quickly or risk being left behind. If you want your business to stay ahead of the curve, you need to be aware of the top data and analytics trends that are disrupting business as usual. Here are five trends that will have the biggest impact in the coming years.

1) Low Code / No Code Automation Tools

Automation tools are becoming easier to use, not restricted to just the most technical teams at an organization. In recent years suites of tools have matured and grown like Microsoft Power Platform, ServiceNow, Alteryx, and many more that make automation easy for most end users. The thought of automation can be daunting to some because there are so many types like Workflow Automation / Business Process Automation, Data Automation, RPA, and more, and they all have their place.

The easiest way to dip your toe into automation is to use the tools you already have access to, like Microsoft Power Platform. If you have data automation tools, then take advantage of those.

The next step is finding processes and tasks that are suitable for automation. The easiest way you can find automation opportunities is by looking for spreadsheets, which I talk more in-depth about in Why Spreadsheets Are a Sign of a Major Problem. A quick summary is that a spreadsheet acts as a bridge solution for 3 significant problems – Systems & Applications don’t move data between them, the system the user is using lacks functionality or features, or a breakdown in the process itself. By automating even small manual tasks with new low code tools, you improve productivity and free up time for more value-added activities.

2) Data Visualization Will Be the New Excel

Data visualization has been around for a long time, but the tools and techniques have recently undergone a revolution. The days of static charts and graphs that are hard to understand, lots of coding, and 3D pie graphs are gone.

With the new generation of data visualization tools like Tableau, Qlik Sense, and Power BI, the average business user can interact with data in ways that were impossible before. The ability to ask more nuanced data questions, drill down, explore, or connect disparate datasets with visually rich, clear graphics uncovers insights that inspire new ideas and drive better decisions.

Business users no longer have to wait for the reporting department to build a new dashboard. Every person in an organization can now have tools available to tell their story with data.

3) Democratization of Data

Data democratization – the idea that everyone should be empowered with access to data regardless of their role – is more relevant now than ever. Making data available to everyone in an organization, not just the people with technical skills speeds up the pace of decision-making and enables a data-driven culture.

The first step in data democratization is ensuring that data is available and of good quality. Building out a data ecosystem that is trusted and accurate can be a challenge for organizations with a lot of legacy data. Data availability can be achieved by consolidating data into a data warehouse or data lake or using modern data approaches like streaming and event-driven architectures. This streaming and event-driven architecture can help speed decisions by bringing data closer to the decision point. What can’t be overlooked is that it isn’t only about speed but quality and trust in the data.

The effort of standing up a widely accessible, trusted data infrastructure pays for itself with faster innovation, more engaged employees, and more-informed business decisions.

The major trend in this area causing this is the shift to data products, and organizational architectures like Data Mesh and Data Fabric start to overtake Data Warehousing. You’ll see more agile approaches to data applied and an increased speed of productized data.

Uday Joshi, one of our talented data strategy consultants, wrote a great piece around the Shift to Decentralized Data Ownership. A rising trend will help tear down the walls erected around data.

If you’re looking for help around adoption and creating a data-driven organization, reach out to us. Thought Logic’s Data and Analytics practice would be happy to assist you in turning your data into information and driving the adoption of those tools.

4) Data Management Becomes a Business Priority

With wider access to easy-to-use visualization tools, democratized data, and automation, it becomes imperative that everyone is working from the same data sets and using the same denominator. You don’t want marketing and finance groups reporting the same KPI with different numbers.

Data management ensures there is a single source of truth for the organization that everyone can trust. The days of every department having their data warehouse or a data store are coming to an end and more implementations of data lakehouses and even data organizational changes like data mesh or interwoven approaches like data fabric are adopted. The benefit of this is that it allows for an organization to move faster and with less risk.

The focus on data management will increase as the landscape changes, and companies are looking to use their data as a competitive advantage. Along with this, the tools and processes will also need to change. The goal is to make data management easier and more efficient to scale with the business.

Troy Blackman, who helps lead our Data Management capabilities at Thought Logic, wrote about Your Bad Data is Costing you BIG and why it is important to make sure you’re thinking about data management and the impacts around ignoring it in your Data Strategy.

5) Empowered Analytics

Self-service analytics will not be what we envision today. It should be called “Empowered Analytics” rather than self-service analytics. I’m still working on that name, but empowered analytics enables business users to access data and answer their business questions without help from the IT department or data scientists.

This will become more prevalent as data analytics tools become more available to more technically savvy business users, and data democratization will help break down walls of large centralization and monolithic data architectures. The goal will be to answer questions about their company and be alerted of any issues in the near term.

If you think of a good dashboard, it usually answers 60-70% of the end-user’s questions about the intended area, but there is a huge, long tail of questions that are hard to answer or fit all in the dashboard. The future of dashboard design will start to become a search with proper metadata to answer the user’s question. Think about Yahoo vs. Google before Google dominated. Yahoo was a directory, but when you had a question or needed a specific answer, you turned to Google because they offered answers. The new self-service will include ad-hoc analytics but it will be search functionality that will help users find what they are looking for. I touched on some of this in, The Rise of Self-Service Analytics which focuses more on ad hoc reporting.