Data collection and its analysis are crucial in directing market shifts and changes. The organisational journeys of businesses across every sector are being shaped by advances in Big Data Analytics, Data Science, and Artificial Intelligence.

Here are some of the Data Analytics trends we should look out for in 2023.

Artificial Intelligence.

Machine Learning, Artificial Intelligence, Robotics, and Automation have revolutionised the way businesses operate.  These technological advances in AI are assisting businesses as they strive to get a better understanding of the data they collect.  Advances in Artificial Intelligence can be used to boost business value. It can be used to forecast demand, accurately estimate goods requirements, and improve customer satisfaction.

Data Democratisation.

Data democratisation works to empower everyone within a business to interact confidently with data no matter the level of technical expertise. People across all departments can make better business decisions that enhance its products or services.

Data Democratisation also relies on AI solutions. AI’s beyond human capabilities help to ensure data inclusivity and promote technical justice by facilitating business growth among emerging business environments. A democratised data environment equips employees with the right tools to understand and harness the potential of big data.

Edge Computing.

Edge computing has created a wealth of opportunities, enabling computing and data storage to be brought closer to where the data originates. As a result, data is more accurate and manageable. It also reduces costs and provides faster insights and actions.  Indeed, the pace of data processing at the edge will increase by an estimated 75% in 2025. It currently stands at around 10%.

It has other benefits too that extend into our everyday lives. IoT devices that are embedded with edge computing are faster, more agile, and more flexible; able to perform real-time analytics and enable autonomous behaviour.

Augmented Analytics.

Augmented analytics uses machine learning and natural language processing to automate and process data. It also allows us to gain insights from data that would otherwise be handled by a data scientist. Augmented Analytics helps analysts and users perform thorough analysis and data preparation tasks, even without possessing deep analytical expertise.

Data Fabric.

The data fabric is a set of architectures and services that provide consistent functionality across multiple clouds, delivering an end-to-end solution.  Data Fabric creates a common practice that can be scaled across a range of on premises cloud and edge devices.

Data fabric also helps improve the use of data within an organisation.  It has been proven to be easy to use, easy to repurpose, and can be combined with different integration styles and other advancements. As such, Data Fabric lessens the design, deployment, and operational data management tasks in businesses by up to 70%.

Data-as-a-Service (DaaS).

DaaS is a cloud-based software tool used to analyse and manage data. Essentially, it allows customers to access, use, and share digital files over the internet.  It will lead to a better rate of productivity within a business, especially regarding big data analytics. It will facilitate data sharing across departments and industries, making business review tasks easier for analysts.

Since the boom of cloud-based solutions to modernise infrastructure, DaaS has become more and more popular when managing, integrating, storing, and analysing data.

Natural Language Processing (NLP).

NLP focuses on the interaction between human languages and computers. NLP is anticipated to become increasingly important in monitoring and tracking market intelligence as businesses use data and information to formulate future strategies.

Data Analytics Automation.

Data Analytics Automation involves automating analytical tasks with computer systems to minimise human involvement. It has already paved the way for analytic process automation (APA), which has been credited with unlocking predictive and prescriptive insights for quicker wins and higher ROI. Data Analytics Automation technology will accelerate productivity and improve data utilisation. As such, it will have a significant impact on the productivity of many enterprises over 2023 and beyond.

Data Governance.

Data governance is the process of ensuring high-quality data can be shared securely while complying with any regulations related to data security and privacy.  Working without a data governance strategy compromises data protection and maximizes the value of data.  It also puts the business at risk of non-compliance fines and sanctions, poor data quality, missed opportunities, and poorly trained AI models.

As businesses come to rely more heavily on data throughout 2023, having a solid data governance strategy will only become more crucial.

Cloud-based Self-Service Data Analytics.

Self-service data analysis is set to become the next big thing in data analytics through cloud-based management systems.  Self-service data analytics is being heavily adopted across HR and the financial services sector. The aim is to democratise the information, allowing all users to have direct access to the information they need.  Self-service analytics has the power to advance organisations in 2023. It gives employees across every department the power to communicate through its data, thus enabling quick decision-making and strategic evidence-based actions.

Data analytics in 2023.

Organisations of every size and across every sector are data-driven. By offering SMEs the same opportunities as their larger competitors, many of these trends will help smaller businesses scale and evolve in 2023.

AI has paved the way for non-tech folk to improve the digital offerings of its business. Trends such as data democratisation, and augmented data analytics will allow users of all abilities to be more data focussed in 2023 and beyond.

With such volumes of data businesses hold in 2023, the risks increase. Data breaches and non-compliance surrounding data have heavy financial sanctions that have the potential to bring SME organisations to their knees. Trends such as data governance are a direct reaction to businesses’ access to data in volume and we can only expect these trends to strengthen over the coming years.

Can we help?

Are you a business leader looking to grow your data team? Perhaps reading this post has made you stop and think if your data strategy reflects these emerging trends.

We can help you find the data talent to meet your data needs in 2023. Reach out today.

Did you enjoy this article? You may also find this one interesting, the 5 Data Mining trends you cannot ignore in 2023.

About the author: As a founder of Ignite Digital Talent, I lead our brilliant team to ensure we deliver time and time again for our clients. I also stay closely networked with industry influencers to ensure we are well placed to understand the issues and challenges our clients face.

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