Here are a few trends that will help you adjust your big data strategies for 2021:

• Data quality and modeling

Data quality remains a key aspect in any data strategy, governance or management. It will continue being the reason for trusting data and making accurate business decisions. Organizations can enhance data quality by creating centralized rules and standards of data representations that will alleviate the challenge of data silos or fragments. Machine learning algorithms will become critical in enhancing data quality by improving inputs and minimizing dubious outputs. Centralization methods standardize data modelling and serve as a foundation that eliminates data silos.

• Accessibility of data

Accessible data is everything to an organization. It goes hand-in-hand with quality and modeling and is much more useful to an organization. The challenge to many enterprises, however, is that they struggle to unify all sources of data. Although the previous years saw more concentration on building data lakes, 2021 will be about housing data and making it accessible through various tools that will enhance visualization, analysis and predictive modelling. With a strategy that will improve accessibility, you will open limitless possibilities for every business aspect and operations.

• Remote access

Lockdowns have though us the importance of remote data access. In addition to unifying data, enhancing the quality and ensuring it is accessible for decision-making, enabling remote access is the next big thing. Modern big data strategies must concentrate on building platforms that support both proactive and reactive concerns while at the same time, being accessible remotely. Sadly, remote data access is challenging because hackers are always waiting to exploit vulnerabilities in remote access capabilities. While ensuring data is accessible remotely, organizations must be vigilant to avoid attacks such as ransomware and exfiltration, which exposes critical data on the internet. This is where backups help. You must account for those accessing materials and devices that they use.

• Big data intelligent apps

Any big data strategy must put in mind the rising number of intelligent apps that use machine learning and AI technologies.  These applications will increase in 2021 going forward with the sole purpose of analyzing behaviors of individuals to enhance product and service provision. One typical example is recommendation engines that are now common in entertainment and e-commerce apps. Therefore, you must have a strategy that incorporates some level of intelligent apps to boost sales and help customers make a choice.

• Data security

I could not come to an end of this without mentioning the importance of data security. This aspect has been the main area of concern for decades and will continue being so in future. Protecting data assets is key to any organization, mainly because of the value of data and regulatory repercussions that emanate from data breaches. With the demand for remote user access, security concerns increase as people may download and manipulate data. A data security strategy must ensure data integrity, authenticity, availability, confidentiality, utility and sovereignty. All these can be handled by having a robust data security strategy.