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Data trends: Six ways data analytics moved forward in 2022

Data trends: Six ways data analytics moved forward in 2022

While the growing power of data has made data analytics a priority for all business leaders, harnessing the true power of data isn’t a straightforward process. 

Businesses have more data than ever, with 97 zettabytes of data currently in the world and more being created daily. However, data management is a struggle, and not every business leader is making money with their data.

In this article, we will look back at 2022 and all the data analytics trends and advancements we saw. We’ll examine trends from all areas of analytics and look at everything from data security, Business Intelligence, and machine learning to data privacy, data sharing, and data governance.

We’ll break down this year in data to help your business understand where its most useful applications have been. Let’s get started. 

A look back at data science in 2022

Predictive analytics

Big Data has been a hot topic for many years, and Big Data analytics has always been fundamental for large businesses that want to have a competitive edge.  

While most analytics tools discover patterns and help you identify areas for improvement or opportunity, predictive analytics goes even further. 

Predictive analytics is becoming more popular with data scientists as it examines both current and historical data. Businesses using predictive analytics can use historical data to better understand customers’ habits. Meanwhile, they can also identify possible obstacles that may occur in the future through a combination of current and historical data.

Predictive analysis is extremely efficient in using customer data to predict responses and help you adjust your business strategy accordingly. 

​​Edge computing

Edge processing is defined as moving processes to a local system such as an IoT device or a server. Edge computing adds computation to the mix. It reduces the long-distance connection between your customer and your server, and it will be one of the biggest trends in data science in 2023. 

Part of what has fueled this massive shift to edge computing is the success of IoT devices in residential and industrial spaces. Concepts such as the smart home and inventory tracking have opened the door for edge computing across these massive industries.

As these devices become more commonplace, we expect this trend to continue to grow in 2023 and beyond. 

A look back at data dashboards in 2022

B2B performance management 

Managing organisational performance requires a central space to view your data. This is where data dashboards come in. While data dashboards have been around for a long time, we have seen them evolve significantly in 2022.

B2B businesses increasingly use the “cockpit” model that integrates data in one place. Business leaders can derive insights from clear, compelling dashboards and translate them into actions that deliver profits. 

The cockpit model for data dashboards aligns staff across the entire business toward company goals and establishes a common commercial-performance language.

B2B cockpits deliver in many ways, helping with the development of analytics, allowing granular performance data to be easily organised and used, and encouraging a data-driven culture. 

Target setting for sales teams 

Another major application for data dashboards in 2022 has been to help sales teams set and deliver goals. By harnessing the power of data-driven culture and interactive dashboards, businesses can build a clear view of their goals and help the sales team achieve them.

Whether it’s topline growth or margin expansion, data dashboarding is allowing more businesses to find and track the right metrics for their sales. Not only that, but tools such as Vizlib allow for data dashboards that are accessible to those in all areas of your business. Your sales team won’t be overwhelmed by swaths of data but rather motivated by clear visualisations of progression in their sales and an understanding of how their work impacts the business. 

Data dashboards are allowing sales teams to create more realistic goals. By incorporating information such as historic revenues and estimates of customer lifetime value, teams get a more comprehensive view of how things could improve.

It’s no longer enough for business leaders to set targets by adding a percentage increase to the previous year’s sales. Today’s data-driven approach should be informed by predictive models that include granular data from multiple sources and include external market factors. 

In addition, with a predictive model, targets can be more regularly updated and adapted to market influence and product. This practice can help establish “fair” target setting and reduce pressure on your sales team, especially in uncertain times such as during an economic downturn or a global pandemic.

A look back at data analytics in 2022

Embedded analytics

Embedded analytics has been a popular topic among data analysts this year, and its popularity will likely continue into 2023 as well.

Embedded analytics does what you might expect – it amends analytics. Placing analytics within a workflow or application makes it possible for the user to take action without having to exit the workflow. 

Embedded analytics provides a more seamless data experience for users and enables your employees to make faster decisions and reduce errors. In addition, embedded analytics can also help e-commerce businesses to improve sales through the use of smart product recommendations.

We are seeing the barrier to entry for embedded analytics continue to lower. Modern analytics solutions such as Qlik have embedded capabilities built into the tool. Historically, embedding analytics into these types of solutions required stretching the possibilities of such tools beyond what they are recommended for, but that is no longer the case. As such, more businesses can harness the power of embedded analytics without any downsides. 

Headless BI (Business Intelligence) 

Headless BI has been a hot topic among data engineers this year. The rationale behind headless BI is that all data transformations, dimensions, etc., should be in a central layer that is decoupled from the presentation layer. 

This central layer means that any BI or data visualisation tool can connect and gather data from your data points to display them in one single source of truth. Headless BI is essential to the idea of well-built and accessible data. 

Shift seamlessly into a data-driven business model

Last year was busy for data analytics, and the pace of change is set to get even faster in 2023! Smart business leaders will need to be more focused than ever on their data analytics in the coming year if they are to stand out from the crowd. If you are looking to propel your business into the modern era of data analytics, why not reach out to Vizlib? 

See how Vizlib can extend the capabilities of Qlik to help your business march toward the future, with confidence and clarity. Democratise your business data today with Vizlib. Sign up for a free trial!

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