Data platforms in 2024

As featured on BusinessMirror: Data platforms in 2024

Data-driven decision making is a core ambition for most modern organizations to effectively understand current performance, identify risk and plan for the future. Yet many organizations remain overwhelmed by the amount of data they have. Despite investing in many data platforms and technologies, business benefits haven’t always eventuated. Getting rapid access to the right data, and in a form where it can be quickly analyzed and interpreted, is still a challenge.

So, do organizations need to invest in new data platforms to create business-changing benefits? Do cloud native solutions provide the best option? Or are data meshes the right way to move forward?

Many organizations have chosen to address data warehouses and data lake challenges by moving towards cloud-native database-as-a-service environments. These provide a single secure platform for an organization to store, manage and analyze its data using a range of data analysis and manipulation tools.

Cloud-native data environments offer several benefits over traditional on-premises data environments. Some of the key benefits of cloud-native data environments include:

• Scalability: Cloud-native data solutions can easily scale up or down depending on the needs of an organization, allowing for more efficient use of resources and cost savings.
• Agility: With cloud-native data solutions, data can be accessed and analyzed in real-time. They also have enhanced data ingestion capabilities.
• Cost-effectiveness: Pay-as-you-go pricing models can be more cost-effective than traditional on-premises data environments, as organizations only pay for the resources they use.
• Security: Cloud-native data solutions provide advanced security features, including multi-factor authentication, encryption, and data masking, to protect sensitive data.
• Data sharing: The cloud enables data to be easily shared between different teams and departments within an organization, as well as with external partners and customers.
• Performance: A cloud-based architecture enables faster data processing and analysis, leading to faster insights and better decision-making.
• Ease of use: Many of these technologies have user-friendly interfaces and SQL-based query languages make it easy for non-technical users to access and analyze data, reducing the need for specialized IT skills.

Data mesh is a relatively new concept in the world of data management and integration. It is a data architecture approach that emphasizes the free flow of data between different systems and applications within an organization. Data mesh aims to enable data to be shared and accessed across different teams and departments without creating data silos or relying on centralized data repositories.

A data mesh architecture offers several benefits in addition to those embedded in a cloud-native data solution. Some of the key differentiating benefits of a data mesh architecture include:

• Decentralization: Data is decentralized, which means that it is distributed across different systems and applications. This makes it easier for different teams and departments within an organization to access and use the data they need.
• Agility: Organizations can be more agile and responsive to changing business needs using a data mesh. By breaking down data silos and enabling data to flow freely between different systems and applications, organizations can make better use of their data and respond more quickly to changing market conditions and customer needs.
• Flexibility: A data mesh architecture enables data to be exchanged and consumed in a decentralized way. This makes it easier for organizations to integrate new systems and applications, and to experiment with different data sets and analysis techniques.
• Cost-effectiveness: This approach reduces the need for expensive data warehouses and other centralized data repositories. By enabling data to be stored and accessed in a decentralized way, organizations can make better use of their existing infrastructure and resources.

If an organization is primarily focused on managing and analyzing structured data, a cloud-native data solution may be a good choice. These solutions are designed to handle large amounts of structured data, and offer several benefits including scalability, agility, cost-effectiveness, and security.

On the other hand, if an organization wants to break down data silos and enable data to flow freely between different systems and applications, a data mesh architecture may be a better choice.

It's important for organizations to carefully assess their data management challenges and goals before making a decision. In some cases, it may be possible to implement both a cloud-native data solution and a data mesh architecture, depending on the specific needs of different teams and departments within the organization.

Ultimately, the most effective data management strategy will depend on a range of factors, including the organization's size, industry, data needs, and IT infrastructure. Organizations should work with experienced data management professionals to develop a customized strategy that meets their unique needs and goals.