Five data analytics trends that will shape BI in 2023

1 January 2023

Artificial intelligence (AI) and machine learning (ML) have exponentially increased the power of data analytics frameworks and business intelligence tools. Features such as predictive analytics, forecasting, sentiment analysis, and engagement scoring make today’s BI tools capable of delivering intelligent and accurate decisions backed by data.

Let’s explore the latest trends in data analytics that will become prominent throughout 2023. 

1. Integrating data silos, resulting in richer input data for business intelligence tools

Businesses will feed Business intelligence tools with two types of data: processed data extracted from business applications such as an ERP or a CRM or unprocessed raw data from databases such as spreadsheets.

Processed data has a well-structured schema and metadata that helps the BI tool provide more accurate analytics. Yet, many businesses store data in both formats and then feed it to the BI system. Unprocessed data is often passed through ETL systems or datalake where their structure matches that of the BI system. This dual nature of data exists because of silos, and the data silos exist because of disparate systems within an organization.

For example, an organization that collects data from its website, social media accounts, and advertisements uses different platforms for data collection. These data collection points are disparate (thus creating data silos), and businesses collate the data in a spreadsheet and feed it to the BI tool.

Alternatively, businesses can integrate their platforms using a CRM that becomes a single data collection point, and the CRM can feed the processed data into the BI tool to avoid data silos and duplication. The latter reduces data leakage, maintains a single schema and structure, and passes important metadata to the BI system. In 2023, more businesses will implement such unification systems in their organizations to enrich data analytics.

2. Infusion of artificial intelligence and machine learning

AI and ML will be the backbone of modern BI systems.

Traditionally, analytics systems graphically portrayed tabular data. Businesses had to derive insights from these visual representations. This is how Google Analytics worked for a long time; it collected website traffic data and categorized it into visual tables, charts, etc.

With AI and ML, analytics systems can go a step further and draw insights from data—action users had previously executed manually. The newer version of Google Analytics (GA4) does not just present visual data; it also gives the system’s inferences for this data.

BI systems in 2023 will rely more and more on AI and ML for accuracy, and it will help businesses create smarter, more reliable systems.

3. The system will convert insights into action

Modern systems can offer analytics and their interpretation of these analytics or insights. Businesses are responsible for applying these insights in the real world and taking strategic actions.

An analytics trend that will catch on through 2023 and beyond is converting insights to action within the business intelligence tool. BI tools are now implementing features that allow users to trigger actions within the system. The BI systems decide the course of these actions using available data.

Platforms such as Google Ads (which isn’t a BI tool per se but is a good example here) already have features such as ‘recommendations’ and ‘auto recommendations’ that achieve this very same result. The platform analyzes acquired data to deliver recommendations (the next course of action) that the user accepts or rejects with a click. This allows users to take a hands-free approach and trust the system to make data-backed decisions.

Based on data analysis, BI systems will implement similar features and trigger changes in connected applications.

4. Context-based analysis

Another trend we will see in 2023 in data analytics is context-based analysis. This uses not just data points but also the context behind each data point to deliver insights and actions.

For example, businesses might experience a dip in sales during specific periods of the year. A BI tool can forecast this dip by analyzing historical data. It will present businesses with actionable insights and the course of action well in advance to chart out a contingency plan.

Context-based analytics can tell why these data points act the way they do. Maybe a large part of the sales come from a particular region which experiences bad weather during that period, so people limit their shopping efforts. This context is then added to the insight and is a feature that will become more popular within BI systems in 2023.

5. Will enable real-time decisions

With data analytics, time is money. The longer businesses take to understand insights and create an action plan, the more money businesses will lose as they deploy outdated processes.

Decision-making cycles will shrink as we move forward in 2023, thanks to AI and ML and their insights-to-action capabilities. With the increased accuracy and reduced turnaround times of BI systems, businesses can make decisions backed by real-time data and implement them into their workflows.

Final words

Organizations are always looking to enhance processes; the right way to achieve this is by making data-backed decisions. A business intelligence tool is not an optional asset anymore; it is a mandatory implementation irrespective of business size or type.

Richer data analytics frameworks push BI tool developers to enhance their products using modern technology such as AI and ML. It will be interesting to see which trends will become standard features and which new trends will take place as we move through the year.

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