More so than ever before, businesses understand the importance of business analytics. They’re no longer asking why business analytics is necessary; they’re asking how to implement it. Luckily, gone are the days of trawling through spreadsheets and needing specialist education to gather data. Now, thanks to the likes of artificial intelligence, cloud capabilities, and other technological advancements, there are plenty of options. Aside from these methods, businesses need to consider GDPR and data privacy in their data analytics. If you’re running a business and looking to stay agile, continue reading to understand the top trends in the data analytics space.
After giant companies including Facebook and Google suffered huge data breaches, the general public are much more concerned with how their data is being used. When it comes to business analytics, privacy has to be at the forefront of practices from the beginning. Therefore, legislation blew up all over the place in 2018, including the California Consumer Privacy Act and the General Data Protection (GDPR). These pieces of important legislation set out the benchmark for data privacy across certain areas. If businesses fail to comply, they become vulnerable to hefty lawsuits. If you want to take a deeper dive into the data analytics space, we suggest an MSc management and analytics at Aston University.
Augmented analytics refers to the enablement of artificial intelligence (AI) and machine learning in the generation and preparation of data. Through data augmentation, the world of business analytics is evolving from data reporting telling us what did happen to what will happen. In simple terms, augmented analytics helps businesses to deal with the enormous data sets begin derived from the implementation of the Internet of Things (IoT).
Cloud resources have seen exponential growth over the last couple of years, and through 2021 and beyond it will continue to thrive. Already, customer information and important business documents are being shared through the cloud. With that, the data analytical process is going to start taking place through the cloud. According to Gartner, the existence of “no-cloud” policies are just as obsolete as “no-internet” policies. Despite the wording, this doesn’t mean that everything will take place on the cloud. Predictions state the most common format will see a mixture of internet and cloud-based data storage.
Despite the continued rise of cloud technology, it comes with its own set of pitfalls. The most prominent issue is that the storage of business data on the cloud puts it out of complete business control. Therefore, significant security practices need to be adopted to limit the chances of cyber-attacks. Further, if the internet goes down and information is stored on the cloud, businesses will lose access.
Predictive and prescriptive analytics are hot topics in the business analytics space. This is because businesses can take a look into the future and be better prepared to meet customer needs. Predictive analytics looks at current trends and helps us to understand what will likely happen in the future. Prescriptive analytics, however, helps businesses to understand why trends will happen. When businesses understand why future trends will happen, they can develop tactics to help curb the tide and take control.
Businesses have been faced with large conversations surrounding data management and security. This comes on the back of the Cambridge Analytica Scandal, which saw a breach of around 87 million Facebook accounts. As well as this, there have been plenty of other data scandals, including the Equifax breach in 2018. Breaches like this have led businesses to take data management extremely important to operations. This means that businesses must continue to secure data and define the way they use it and collect it.
Alongside data management and security, businesses need to allow consumers access to their data, as dictated by GDPR. This is why every legitimate website you browse will ask you what information they can collect. Without consent, businesses aren’t able to store data. Further, the authorisation of data collection isn’t absolute. If someone asks for data, under GDPR, businesses are legally obliged to hand it over and delete it on their end.
Embedded analytics integrates analytics into all-in-one software, which streamlines processes and reduces the need for standalone software. For instance, if you take a look at Salesforce, you will see that data analytics including customer insights and behaviours are embedded throughout the software. With that, users have access to only the information they need. By doing this, they won’t be overwhelmed by irrelevant data, which will improve productivity.
AI is being used to improve the effectiveness of customer experience. For example, the majority of websites adopt chatbots for online customer contact. These AI systems are created by large data analysis. After all, they need something to learn from. The use of chatbots bleeds into business analytics through the process of language processing. In this, interactions are stripped down into raw data and used to increase the chatbot effectiveness. For instance, if a customer contacts a chatbot that can’t answer a query, the data can be relayed through a data analytics solution where it can be used to improve the intelligence of the chatbot. Therefore, the next time a customer approaches with the same question, they will be able to answer.
Businesses are collecting huge amounts of data now, so it’s important to practice data quality management (DQM). From the point of collection, all the way to the distribution, data needs to be optimised. Data managers will need to assess data in terms of validity, uniqueness, consistency, and completeness. In simple terms, the data manager tracks data over time and makes sure it’s being used effectively. Data analytics is central to modern-day business operations, and the focus has shifted from why it’s useful to how to implement it. Through the end of 2021 and beyond, cloud technology takes centre stage, with the majority of business analytics taking place in the cloud. Further, predictive and prescriptive analytics will overtake descriptive analytics to help businesses understand future trends ahead of time.