As we step into the new year, it’s crucial to examine the key business and IT trends that are set to exert their influence on data management throughout 2022.

Navigating the Post-COVID Landscape

The lasting impact of COVID-19 continues to reshape the way we work, shop, and interact. With variants like Omicron still on the horizon, we anticipate that remote work and online shopping will remain preferred options for many, at least in part.

From a data management standpoint, the focus will be on leveraging automated collaboration tools to support remote workforces effectively. These tools not only enhance teamwork but also facilitate the adoption of agile approaches across distributed teams. Companies are increasingly seeking solutions that enable easy data discovery, access, and management without relying heavily on internal subject matter experts. Ensuring data security for remote teams without hindering productivity will be another top priority.

The Shift from Monolithic ERP to Specialized Applications

Recent years have witnessed a significant shift away from monolithic Enterprise Resource Planning (ERP) systems towards specialized, often cloud-based, applications. Traditional ERP vendors are facing stiff competition from the likes of Workday (HR), Coupa (procurement), and Salesforce (CRM) in their respective domains.

This shift necessitates careful consideration of data integrity. Organizations must address data quality and master data management issues as they transition data from legacy ERP systems to these new specialized platforms. Understanding the metadata of your ERP system becomes paramount in planning a seamless data migration.

Embracing Cloud-Based Analytics

At the same time, companies will continue to battle for the hearts and minds of customers, through data analytics.

Building upon the trend of specialized applications, cloud-based analytics has become the new norm. Successfully migrating data to the cloud presents its unique challenges. Untangling on-premise data architectures and replicating essential capabilities in the cloud is essential for a smooth transition. Automated metadata harvesting and lineage tracing for existing data stores are critical components of this process.

The ever-growing volumes of data and the increasing need for actionable insights will continue to drive the adoption of streaming data solutions. Reliability and traceability will be key concerns in this context. Data privacy remains a paramount consideration, necessitating robust solutions that protect sensitive data while allowing legitimate access. Hybrid cloud environments will require fine-grained access control (FGAC) mechanisms that extend across both on-premise and cloud data repositories.

Navigating Evolving Data Regulations

Data privacy regulations, such as PoPIA, will continue to shape behaviour and strategy in the data management landscape. Additionally, emerging regulations in the EU and the US will aim to govern the use of Artificial Intelligence and other emerging technologies, introducing complexities into existing regulatory frameworks.

Proposed legislation in the US, such as the Algorithmic Accountability Act and the Algorithmic Fairness Act, seeks to regulate systems facilitating human decision-making based on consumer evaluations or involving personal information related to race, religion, health, gender, and more. In the EU, any use case involving biometric identification or operation in critical infrastructure, education, employment, public and private services, law enforcement, migration, or state administration is classified as high risk.

Companies investing in AI solutions must meticulously document the development, training, and performance of AI systems over time. Furthermore, they must demonstrate the quality of the data used in these processes. This places AI governance, data quality, and data privacy solutions at the forefront, offering a shield against regulatory scrutiny.

In conclusion, 2022 promises to be a year defined by adapting to ongoing global shifts while upholding the integrity, security, and quality of data. Staying ahead in the world of data quality and governance is not just a choice but a necessity.

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