What are the advanced data analytics challenges facing European companies in 2022?

Let’s talk about Advanced Data Analytics. What is it exactly? How are businesses using it? And how can you best use it to your advantage?

Milton Nieves

Businesses around the world are becoming increasingly aware of the importance of Advanced Data Analytics. From improved decision-making to increased ROI, there are many benefits to understanding your business' data. For example, it can help you predict potential losses while monitoring your company's overall performance.

So what advanced data analytics challenges are companies currently facing in 2022? To get an idea of what's happening, we compiled a list of current and upcoming challenges. We analysed the potential outcomes to provide you with some ideas for possible solutions — many of which we already use for our clients.

Ready? Let’s dive in.

Challenge 1

Managing volumes and collecting meaningful data in real-time.

A growing number of companies are starting to bet on data. But one of the most prominent challenges they face each day is juggling the volume of data they can handle.

And there's a lot of data out there. So, instead of it becoming a tool to rely on, the sheer volume of data makes it increasingly difficult to drill down and access the knowledge needed the most in real-time. Unfortunately, this is often the cause for some companies that skip essential components of their data tracking by only focusing on the metrics that are easier to collect. The approach leads them to miss out on the data that truly adds value or helps drive business decisions.

The main challenge lies in processing data in real-time. There's a significant gap in the market regarding how data is processed and translated, as it's almost impossible to report on current events. While tracking past data might be suitable for bookkeeping, outdated data can negatively impact timely decision-making.

What's a potential solution?

Building a data culture among employees. That means building data analytics skills and training employees to easily help solve most data analytics challenges, starting with collecting meaningful data. Once employees begin to understand data, they'll know what data is vital to your business. Another solution is to implement a data system that automatically collects, organises, and alerts users about current data processing trends - defining objectives and creating reports that answer some of the most critical questions. Real-time reporting and alerts allow key stakeholders to make decisions based on complete and accurate information.

Challenge 2

Hiring and retaining workers with advanced data analytics skills.

Companies today face a huge challenge: finding and retaining workers with advanced data analytics skills. One reason for that is the increased demand for data managers or data scientists positions, which has skyrocketed due to data and technology advancements in recent years. According to a Gartner report, this trend is only growing and is expected to continue to do so for at least another two years.

What can you do?

A great interim solution is to associate yourself with a company that specialises in advanced data analytics to create a DATA LAB. A LAB allows you to jointly develop a knowledge transfer strategy and create internal capacities in the short and medium-term through the delivery of joint tasks. Of course, the LAB will have more specialised talents on their side, but this will change over time as you start to build out your capacities. Whether it's a mix of your own team and a partner's, having the right talent can help estimate and anticipate risks, assess severity, and solve advanced data analytics challenges. It also helps create a data culture to attract and retain the right talent.

Challenge 3

Easy Data Visualisation to improve data understanding.

It goes without saying: data analysis is meaningless until the numbers tell a story. The data has to be presented visually in graphs or charts to be understood. When creating products or services based on data, you need access to specific, contextualised data, limited to each brand and situation. It has to be focused on people and their behaviours with the capacity for intelligent analysis. But taking the time to pull information from multiple sources to put it into a reporting tool is frustrating and time-consuming. On the other hand, the time, money, and effort to collect and protect data helps make informed business decisions and achieve ROI. So, data visualisation is, essentially, a very critical part of any company's business strategy.

Some options to look into.

Data visualisation tools such as Google Data Studio, Power BI, Tableau, among others, are easy to learn and have a wide range of features. These tools have drag and drop functionality and can also connect to various data sources. They come with intuitive graphs and charts, which help you visualise the data. Some data systems allow the creation of reports at the click of a button. Decision-makers can access the real-time information they need in an easy-to-read and easy-to-use educational dashboard format. With these types of solutions, companies can get useful information that will give them a clear advantage over their competitors. They can attract new buyers, sell more, predict better results, identify new business opportunities and, above all, they're able to grow by being more relevant to their consumers.

Challenge 4

Prepare for a GDPR compliant, cookie-less world.

One of the main concerns of European companies is collecting users' data while respecting their rights and privacy. Firefox has been blocking third-party cookies by default since 2019, while Safari started blocking them in 2020, and Chrome will follow in 2023. When the EU General Data Protection Regulation went into effect in May 2018, every EU website was legally bound to prompt a cookie acceptance banner, explain which data they were collecting (and its purpose) and give the user an option to actively accept, reject, modify or delete their data. Some websites are still not compliant with these regulations, but those who care about building a trustworthy relationship with their users are worried about losing customer insights and valuable information in the near future.

How can you make sure you don’t lose out on important data?

The first suggestion would be to migrate to an open-source, GDPR-centred analytics platform that allows companies to own their data and doesn't install third-party cookies on users' devices; there are already a lot of them out there. The next step would be to adopt a unified data approach combining first-party data with contextual behaviour data and predictive modelling, using AI and machine learning to enhance information and discover lead generation and lead nurturing opportunities.

Data is an essential part of any successful business. But it’s also an ever-changing area that requires you to stay up-to-date with anything from the latest visualisation tools to legal requirements. Need help navigating this space? Let’s talk.