Henry Ford, with the measurement of the time taken on the assembly line, is perhaps one of the first examples of industrial use of data analytics – it is, therefore, neither a new phenomenon nor a result of the computing age. Data Analytics' importance has only increased with the pace of the modern world, computing advancements, and the competitive business landscape.

Crystal gazing towards the 2023 future of Data Analytics gives a sense of firming up trends and emerging new insights. Given the advancements in AI, ML, AR, Edge computing, Cloud infrastructure, data storage, and computing power, it is natural that Data Analytics leverage these. Also essential are the increased requirements in terms of regulatory and compliance issues, customer expectations, competitive pressures, employee empowerment, remote working, ESG, etc., that Data Analytics deliver towards these goals.

The Data Analytics trend that will thus create an impact in 2023 are:

AI data analytics

AI is now coming of age and enabling data insights unheard of earlier. The pharma industry has used AI to shortlist viable molecules for further development. Thus, reducing research efforts and reducing costs incurred on false trials. Similar advantages are now set to be realised across multiple high-performance business sectors and innovative businesses.

Self-service data analytics

Enabling employees to maximise effectiveness and productivity remains the holy grail of business success. Meaningful Data Analytics is set to move from senior management to broader employee sets. This will give customer/supplier / internal-facing employees the power of analytics for enhanced business impact.

Data analytics automation

Automation is another massive trend. It seeks to reduce the set-up time required for repetitive Data Analytics tasks and the associated talent costs by reducing human involvement. This will also ensure consistency and precision in trend analysis and, thus, resultant insights.

Enhanced customer experience

Data Analytics for enhanced customer experience (External and Internal) creates a direct bottom-line impact for businesses. Cross-selling, upselling, and customer loyalty with ease in buying experience will enhance sales volumes. While predicting customer needs in advance will also help improve inventory management and cost reduction.

Edge computing analytics

With the widespread rollout of 5G and faster edge devices – the analytics load will shift towards the edge to enable quicker and cheaper computation. IoT devices will thus be able to react faster and even behave quasi-autonomously.

On-the-go dashboards

The barriers of pre-defined analytics or business Intelligence dashboard constraint will come down to allow for on-the-go dashboards that morph dynamically as per the environmental context and user requirements.

Augmented analytics

Machine Learning and Natural Language Processing will unleash augmented analytics. These will feed into better self-service analytics and customer experience enhancement for widespread applicability and business gains. It will also open the world of advanced analytics to less experienced users, thus boosting the overall usage of analytics.

Data analytics investment

Investment by businesses in enhancing their data analytics capabilities to support the above requirements will also be a strong trend. As a result, hardware, cloud, software, and talent demand for data analytics will shoot up, and prices may not fall rapidly.

Disruptive business environment

With the power of Data Analytics and new insights, we will likely see more businesses get disrupted. Thus, the organisation must watch out for emerging competition that makes existing service models extinct. Natural Language Processing will be a capability that may lead the charge in this direction.

Given the broad scope of data analytics usage and impact, the most significant data analytics trend for 2023 will be the certainty of business focus for survival and growth. In most cases, customers will see a more responsive world (with the rigid fence in case of special attention requirements). Employees will be supported with decision-support tools that make actions less risky while challenging their job roles. At the same time, data analytics experts can look forward to expanded workloads with enhanced demands and rewards.

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