Focus areas for data and analytics in 2022

January 4, 2022

Like all technology, big data is progressing, and as we start the new year, it is an ideal time to explore what opportunities exist and what areas need improving. This year represents a critical time for big data, AI and analytics, with more businesses anticipating progress and better results for their organisations. Here are some of the areas to consider in big data this year:

Creating a data retention policy

Many businesses have overlooked discussions concerning big data retention or failed to make time to tackle this area. With global data expected to increase considerably in the next few years, and big data making up the bulk of that information, 2022 is the time to create big data retention policies and disregard the data not needed.

Defining the role of big data in the wider data landscape

To establish information across an organisation and ensure data is available for everyone for analytics and decision making, IT teams should ensure big data and other structured data in a business connects and links to all areas.

Utilising additional no-code analytical applications

Using no-code reporting tools for analytics and creating additional reports quicker for end-users and reducing work pressure on IT teams.

Reassess the true value of current applications

While it’s a positive step to launch analytical tools, businesses must ensure it works as well for the organisation as it did a few years ago when it was first introduced. Businesses are evolving, and it’s likely requirements will change in terms of what analytical solutions a business needs now compared to a few years ago. This year it would be beneficial to review the effectiveness of existing analytical tools, measure their performance and assess whether they are meeting the needs of the business.

Create an application and data maintenance strategy

As with structured data and other systems, those utilising big data and analytics require consistent maintenance. Yet many businesses implementing analytics and big data lack any structured processes for maintenance. Big data and analytics have reached a level where maintenance processes are needed.

Upskill and Training for IT

To support big data and analytical operations, new IT skills are necessary for IT professionals. Training may include further development on data science, analysis, big data storage and focusing on skills with new tools, such as no-code analytics.

Assess privacy, security and trusted sources

Big data can be acquired from several third-party sources. These require constant reviewing to ensure they meet corporate security and privacy guidelines. This review should also apply to internal data within a business.

Measure vendor support in big data and analytics

Many vendors provide big data and analytical tools but do not offer the support required for a business. It’s vital to work with vendors that generate sufficient support for your team and additional guidance for important projects.

Ensure your big data and analytics supports the overall customer experience

Nearly every business is committed to improving the customer experience. A core part of this process is establishing customer-focused automation and assisting customers in getting requests, questions and answers. Automating customer-focused systems that use NLP and AI to understand customer behaviours and engage in conversations are still in a stage of development. Businesses that focus on enhancing NLP and AI performance within these areas will undoubtedly see the benefits in the future.

Leaders must review big data and analytics plans

As these technologies have matured, it is now time for senior leaders and other stakeholders to reassess the progress of AI and analytics and ensure a business has to secure support from the top.

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