The Future of Business Analytics: Emerging Trends and Technologies
Business analytics has always played a critical role in helping companies make informed decisions. However, with the ever-increasing amount of data available, businesses need to adapt to new emerging trends and technologies to stay competitive.
The future of business analytics is rapidly evolving, and keeping up with the latest trends and technologies is essential to remain ahead. In this article, I will explore the top emerging trends and technologies in business analytics that are shaping the future of the industry.
Historical background
- 1950s and 60s: The first computers were used for data processing, paving the way for modern data analysis. IBM was a leader in the development of early computer systems during this period.
- 1970s: Decision Support Systems (DSS) were introduced as computerized models that enabled businesses to make data-driven decisions. Oracle and IBM were among the pioneering companies in the development of DSS.
- 1980s and 90s: Data warehousing became popular, allowing businesses to store and analyze large amounts of data. BI tools with graphical user interfaces (GUIs) and ad-hoc reporting capabilities were developed. Solutions like Teradata and Microsoft SQL Server were leaders in data warehousing solutions.
- 2000s: Business Intelligence (BI) tools such as dashboards and scorecards were introduced, which were more user-friendly and accessible to non-technical users, making it easier for decision-makers to visualize and interpret data. Tableau, Power BI, and QlikView were among the companies that revolutionized data visualization during this time.
- 2010s: Big data analytics emerged, allowing businesses to analyze vast amounts of structured and unstructured data to gain insights. Companies like Hadoop and Spark became popular as big data processing frameworks appeared during this time.
The markets for data warehousing and data visualization continue to grow as companies increasingly rely on data-driven insights to make strategic decisions.
- Data Warehousing Market size was valued at US$ 25.96 Bn. in 2021 and the total revenue is expected to grow at a CAGR of 10.7% from 2022 to 2029, reaching nearly US$ 58.54 Bn.
- The global data visualization tools market size was valued at $7.4 billion in 2021, and is projected to reach $19.5 billion by 2031, growing at a CAGR of 10.2% from 2022 to 2031.
- The global big data analytics market is projected to grow from $271.83 billion in 2022 to $655.53 billion by 2029, at a CAGR of 13.4% in the forecast period.
However, the Business Intelligence (BI) landscape is constantly evolving, and new trends with the potential to disrupt the industry are emerging.
1. Actionable AI insights
Actionable AI insights aim to automate the process of extracting patterns and interconnections from data. There is a challenge with traditional data visualization tools: while they provide users with rich visualizations of data, the drawback is that individuals must make decisions independently. In addition, humans simply cannot monitor vast amounts of data from different sources and analyze hundreds of dashboards and graphs simultaneously. The decision-making process still relies heavily on human interpretation and intuition. This can be a problem when it comes to making important strategic decisions, as humans are prone to biases and may overlook important insights.
AI-powered analytics tools, on the other hand, can analyze huge datasets in real time and automatically identify patterns and anomalies that would be difficult for humans to detect.
By providing users with actionable insights that are based on data rather than intuition, AI-powered analytics tools have the potential to revolutionize the way that businesses make strategic decisions.
As this graph shows, AI insights ideally fit into the current structure of how processes are built now and fill an empty niche.
2. More real-time data
The trend of using more real-time data in business analytics has been gaining momentum in recent years, and one of the main drivers of this trend is the Internet of Things (IoT). IoT devices such as sensors, smart meters, and wearables generate massive amounts of data in real time, providing businesses with valuable insights that can be used to make informed decisions. By analyzing this data online, businesses can respond quickly to changing market conditions, optimize their operations, and improve customer experiences. We talked about examples of using IoT in modern production facilities in our report “State of Phygital 2022”.
3. Cloud computing & data security
As in many other industries, cloud computing has been a growing trend in business analytics for several years now. By moving their data analytics processes to the cloud, businesses can take advantage of increased scalability, flexibility, and cost-effectiveness. This allows them to quickly scale their infrastructure up or down as needed, without having to invest in expensive hardware or IT staff. However, with the increased use of cloud computing comes new challenges in data security, e.g. hundreds of millions of Facebook users phone numbers and personal data were leaked online in April 2021)
Businesses need to ensure that their data is protected from unauthorized access and that their analytics processes are compliant with relevant regulations. As businesses continue to rely more heavily on the cloud for their analytics needs, we can expect to see a continued focus on data security and privacy.
Today businesses need to adapt to emerging trends and technologies in business analytics to stay competitive. New trends are emerging, such as the use of actionable AI insights to provide users with data-driven decision-making, the use of real-time data from IoT devices to improve operations, and the shift towards cloud computing for increased scalability and cost-effectiveness. One way or another, the entire business intelligence market will continue to grow as the business is digitalized. Especially there is a good chance that generative AI will disrupt the business intelligence market like many others.
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