The new year is always an opportune time to invest in self-improvement strategies. And while personal changes like eating better, exercising more, or picking up a new hobby may not apply to your IT department, that doesn’t mean there’s no room for resolutions. 

In a recent TechRepublic article, Mary Shacklett urged enterprises to stick to these 10 data resolutions for a better, more data-driven 2022. 

  1. Establish a data retention policy 

By 2025 global data is projected to grow to 180 zettabytes—with big data accounting for 80 percent. In other words, if you haven’t already implemented a data retention policy and eliminated the data you don’t need, now is the time. 

  1. Define data’s role in the data fabric

Bringing big data and more structured data into the data fabric can help companies eliminate data silos and increase data access enterprise-wide. 

  1. Develop more low-code/no-code applications 

Utilizing more low-code and no-code reporting tools for analytics can get data into end-users’ hands faster while simultaneously easing the burden on IT. 

  1. Reassess the business value of deployed applications 

Business constantly changes, and there’s a good chance you have a deployed application that no longer meets business needs. There’s no time like the present to review these applications and course-correct as necessary to ensure analytics are optimized for what you need now. 

  1. Develop an application and data maintenance strategy 

It’s not uncommon for companies to deploy data analytics without instituting procedures for maintenance. However, you cannot afford to ignore this step if you want to safeguard the longevity of your deployment.

  1. Upskill IT 

In 2022, make it a priority for your staff to receive the additional training in data analysis, data science, big data storage, and processing management needed to support your data’s continued maturation. 

  1. Review security, privacy, and trusted sources 

It’s a good practice to regularly review third-party data sources and ensure they adhere to corporate security and privacy standards. 

  1. Assess vendor support in data and analytics

Make sure that the vendors with whom you work are providing active support and guidance for your staff, not only in the use of data and analytics tools but also by providing input during key projects. 

  1. Focus on the customer experience

Improving Natural Language Processing (NLP) and AI performance in customer sentiment and engagement can help companies on their ongoing journey to better, more personalized customer experiences. 

  1. Renew data and analytics discussions at the top 

CIOs should meet with the CEO and other C-level executives to recap the value of data and analytics investments to date and obtain their buy-in for the next steps of the program.

For more insights to help you stay ahead in the coming year, check out this recent APEX of Innovation post on top data science trends for 2022.