Due to COVID-19, the future is a little more uncertain, as business leaders are getting more creative and strategic through the current challenges. But there's no question that business analytics will define the next decade of business in exciting ways.
Business analytics is an incredibly crowded space. Businesses of all sizes and stripes have been looking to harness the power of data for years—even decades.
The future of Analytics has been bright for the past few years. On-premise analytics was being pushed aside for cloud-based solutions, and interactive dashboards were replacing static spreadsheets faster than you could write an equation. Self-service analytics tools allow anybody and everybody to use complex analytics without having a complex degree.
Every year, advancements in technology and the proliferation of data cause a sea of changes in business approaches to analytics. As business intelligence trends adjust to a world where data is king, we could see several changes to how companies approach analytics. While not every company uses the same forecasting methods or software platforms, some of these trends are bound to make their appearance in more companies as 2022 rolls around.
So, to help you remain on top of business analytics trends in the coming year and beyond, we've compiled a list of the top business analytics trends for the following year and beyond.
The Importance of Data Quality Management is growing
Data quality management (DQM) is an emerging category of data analysis—the process of using new and historical data to make predictions about future customer behaviour. DQM programs accomplish this by gathering information from various sources (e.g., social media, market research studies, etc.) and applying advanced analytics to reveal insights about customers' wants and needs.
"Good data quality matters to your effort because it's the foundation for your records, dashboards, and insights. This means your good data can accelerate and amplify the work you're doing, or it can slow you down, confuse your team, and keep you from seeing clear paths to success."
Good data quality is invaluable to a company. High-quality data
can tell stories and make predictions that increase revenue. It's become such an essential tool that its importance has never been higher. A good foundation of high-quality data makes it easier for leaders to make tactical decisions and affect strategy on the fly.
Data quality management (DQM) is the process of ensuring data is error-free at every step of the data life cycle. DQM can start with analysts, but business leaders should oversee it to ensure your team is meeting important business standards. Your customers depend on this information, so it must be carefully analyzed to determine which data needs to be collected and how it can be used to support company decisions.
Scalability requires data management, security, and accessibility
The future of business intelligence is looking bright in the new decade. With new regulations, like "GDPR," being forced by the government and focusing on data compliance, business intelligence is looking at a brighter and more regulated forecast.
Businesses that rely on data to make insightful decisions must constantly strive to manage the influx of new information and ensure it is secure while also making it accessible to all those who need it. It's possible to have expansive archives of sensitive stored data and maintain accessibility simultaneously. The technology needed for this is available today—it just needs to be put into practice.
Augmented Analytics: It's Not Just a Buzzword Anymore
The future of modern business will be shaped by augmented analytics, which is here to stay. Gartner predicts that by 2020, augmented analytics will be the primary driver of new purchases of business intelligence and analytics software. And by the end of 2022, 40% of all data science tasks will be automated.
AI-driven technologies are rapidly changing the face of business analytics. Artificial intelligence will soon be used to augment every data science and analytics activities.ugmented analytics is here to stay, and it will shape the future of modern business.
The activity of integrating data into machine learning algorithms to make predictions and prescriptions based on that data is known as augmented analytics. While augmented analytics may appear to be similar to machine learning and artificial intelligence, it is so much more. Augmented analytics looks at applying predictive algorithms to the data so that our business users can understand the direction of those results and make informed decisions about what to do with them.
Embedded Analytics is growing continuously.
Embedded analytics is an exciting new way to use data. Unlike business intelligence (BI), standalone software that provides information on past events, embedded analytics are tools for making predictions and discovering trends in real-time about a customer's experience. Embedded analytics is designed to create a personalized experience for each person and can be used in any application, from shopping carts to GPS apps.
Embedded analytics is largely defined because the users do not know they are looking at analytics — but they are! Embedded means that the end-user doesn't even realize the analytics they're viewing (and potentially interacting with) is a third-party source of data. For example, an eCommerce company may provide embedded analytics in an online store to show sales trends and forecast future sales based on demographics and buying habits.
AI and Automation Enhancing the Consumer Experience
Have you ever spoken to a chatbot without realizing it? It's more likely than you think, as AI is getting much better at mimicking human speech and behaviour. However, this trend shows no signs of slowing down, with Gartner predicting by the end of 2022, AI will handle up to 45% of all customer interactions.
With customer support costs rising and customer service teams stretched thin, it's becoming increasingly difficult for brands to offer timely and personalized support around the clock. Fortunately, AI-powered chatbots are here to save the day. With a realistic tone and human-like persona, these bots can help close the gap between customers' expectations and experiences.
Business analytics software can make it easier to access data and determine its meaning. Rather than becoming a data scientist, users may be able to "plug and play" all of their data together and have the analytics, predictive modeling, and reporting features completed automatically.
Analytics tools are powerful on their own, but what makes them truly transformative is the highly connected and intelligent world we live in today. The ability to connect to and collect data from a multitude of apps and sources gives you the ability to slice and dice your data in ways that tell every aspect of your company's story."
All told, the future of business analytics is bright and flourishing. As companies become more and more aware of these innovative features, we'll likely see more attention paid to them in the coming years. And hopefully, as this happens, business analytics will continue to thrive and evolve into new and unexplored territories.