Top 10 Data and Analytics Technology Trends

• By Alice Bell
• 01-10-2021
• Trends

While most of the attention paid to the effect of COVID-19 was centred on the rapid transition from on-premises to remote work, the pandemic had a far-reaching influence on every area of the business, including data and analytics technologies, as well. Cloud computing has made data & analytics operations smoother & reliable.

Gartner has identified ten trends that are "mission-critical investments that accelerate capacities to predict, adapt, and react," according to the company's research. It was suggested that D&A executives examine these trends and consider and implement them as needed.

Trend 1- AI that is smarter, more responsible, and more scalable
The use of artificial intelligence and machine learning are essential considerations. Businesses must use new methods to create AI systems that are smarter, less data-hungry, morally responsible, and more robust. Using better, more accountable. And more scalable artificial intelligence (AI), businesses will be able to "use learning algorithms and interpretable systems to achieve faster time to value and greater economic impact," according to a Gartner study.

Trend 2- Composable data and analytics are the watches
It is possible to build flexible and user-friendly intelligent applications using components from multiple data, analytics, and artificial intelligence solutions. This allows D&A leaders to quickly connect the dots between insights gained and actions that need to be taken to achieve their business objectives.

Open, containerised analytics architectures make it possible to build analytics capabilities that are more easily repurposed.

Unquestionably, data is migrating to the cloud and becoming more composable, making analytics "a more agile method to develop analytical applications supported by cloud marketplaces and low-code and no-code solutions," according to Gartner.

Trend 3- Data fabric is the cornerstone
D&A executives use data fabric to handle "increasing levels of data variety, distribution, size and complexity," resulting from greater digitalisation and "more emancipated" customers.

Data fabric applies analytics to the continual monitoring of data pipelines; data textiles "use on-going data analytics to assist the design, implementation and use of various data to cut integration times by 30%, deployment by 30 and maintenance by 70%."

Trend 4- Shifting from large to small and broad data sets
Once the effects of the pandemic had a significant impact on the company, using historical data for machine learning and artificial intelligence models became obsolete. Because human and artificial intelligence decision making is becoming more complicated and demanding, D&A executives need a more comprehensive range of data for improved situational awareness.

As a result, D&A executives must select analytical methods that may better use existing data and provide them with more insight while using less data in the process.

Using small and broad data methods, Sallam stated, "organisations may benefit from powerful analytics and artificial intelligence while decreasing their reliance on big data sets." "By using large amounts of data, businesses may get a richer, more comprehensive situational awareness or 360-degree perspective, which allows them to use analytics to make better decisions."

Trend 5- The use of DevOps
To achieve efficiencies and economies of scale via DevOps and best practices in dependability, reusability, and repeatability, the skills of DataOps, models, and platforms are required. These skills are collectively known as XOps. This also helps to minimise duplication of technology and procedures while also allowing for more automation.

Operationalisation must be handled from the beginning rather than as an afterthought since it causes the majority of analytics and artificial intelligence initiatives to fail. "If D&A executives operationalise at scale utilising XOps, they will allow the reproducibility, traceability, integrity, and integrability of analytics and AI assets," according to the study.

Trend 6- Engineering decision intelligence
As choices become more automated and augmented, D&A executives will be able to make engineering decisions that are more precise, repeatable, transparent, and traceable. Gartner refers to "engineering decision intelligence," which refers to a succession of choices made in the course of business operations, as well as categorised emerging decisions and repercussions, among other things.

Trend 7- Data and analytics as a critical corporate function
D&A is now becoming a fundamental corporate function, rather than a secondary one, resulting from this transformation. D&A is now a shared corporate asset that is linked with business outcomes. According to Gartner, D&A silos are being dismantled as a result of improved communication between central and federated D&A teams.

Trend 8- A graph that connects everything
People, places, things, events, and locations are all connected via graphs, which serve as the basis for most current data and analytics capabilities. Charts are used to discover connections between people, places, things, events, and locations across a broad range of data assets. When it comes to complicated business issues, D&A executives depend on graphs to provide fast solutions. However, charts need contextual knowledge and a grasp of the nature of linkages and strengths across various entities.

The research firm Gartner forecasts that graph technology will be utilised in 80 per cent of data and analytics breakthroughs by 2025, up from 10 per cent in 2021, allowing for more fast decision making throughout the business.

Trend 9- The emergence of the enhanced consumer
Many businesses nowadays rely on preset dashboards and manual data exploration, resulting in erroneous conclusions, wrong choices, and actions on the business users. Users' requirements may be met with automated, conversational, mobile, and dynamically produced insights that can be modified via a preset dashboard, gradually replacing time spent in predefined dashboards.

Trend 10- Data and analytics at the periphery
Information technology (IT) does not provide support for data, analytics, and other technologies since edge computing environments are closer to assets in the physical world and are beyond the jurisdiction of IT. Gartner forecasts that by 2023, data produced, maintained, and analysed in edge settings will account for more than half of the primary responsibilities of data and analytics executives.

Gartner came to the following conclusion: "D&A executives may take advantage of this trend to improve the flexibility, speed, governance, and resilience of their data management systems. The interest in edge capabilities for D&A is being fueled by a wide range of use cases, ranging from providing real-time event analytics to allowing autonomous behaviour of objects."

Competitive pressure is growing for companies to gain consumers and understand their customers’ requirements, optimise customer experience, and establish long-term connections. Companies have to collect and reconcile a client ID with various consumer identifiers like cellular phone, email and address. In their contact with businesses, consumers increasingly use numerous channels. Thus both conventional and digital data sources must be brought together to understand customer behaviour.

Products are the lifeblood of every organisation and are typically the most significant investment businesses. The purpose of the product management team is to understand trends that drive innovation, new products and services on a strategic roadmap.

Conclusion
Companies still struggle with structured data and must be very sensitive to the volatility generated by today's consumers using digital technology. It is only via sophisticated analytics that it is feasible to respond in real-time and make the client feel personally appreciated.

Poor operating management may lead to a host of expensive problems, including a high risk of hurting customer experience and eventually brand loyalty. The use of analysis for the design, process control and optimisation of business operations in products or services production guarantees efficiency and effectiveness to meet customer expectations and achieve operational excellent.

Data and analytics (D&A) technology trends for 2021 have been recognised by Gartner, Inc., as the top ten that may assist businesses in responding to change, uncertainty, and the possibilities that these offer in the next year.