In a fast-moving business world, organizations always need to update their technologies and capabilities to remain active in the competition. The availability of data is an important factor for organizations to gain a competitive advantage in the market. Organizations can efficiently act at the right time and enable them to be flexible by adopting required changes using the available data. Data stacks are one of the solutions that enable organizations to manage, access, and store data. Recently, data stacks have failed to keep up with the organizational data demands and it had forced organizations to search for a new solution, and this had ended up in “Modern Data Stacks”.

What is Modern Data Stack?

The large volume of data processing has become quicker and cheaper after the innovation of cloud data warehouses, which leverage advanced SQL technologies and massively parallel processing (MPP). Along with this, several cloud-native tools and technologies that are low-code, scalable, low cost, and easy to integrate have been developed, and they have collectively come to be known as modern data stacks (MDS).

Modern data stacks majorly focus on enhancing organizational efficiency and discovering business opportunities by analyzing organizational data. Modern Data Stacks (MDS) is made up of several tools and technologies that are used for data management, data analytics, and data delivery. Modern Data Stacks is one of the latest innovations in data integration technology, enabling organizations to save time while focusing on complex tasks. In the world of complex data, organizations require an effective modern data stack to make use of their data. Mainly, organizations make use of modern data stacks to save time that is required for extracting information from their data and to reduce the cost associated with data management. Organizations will be able to leverage analytics for organizational purposes with the help of an efficient data stack that will aid in decision-making.

Major features of Modern Data Stack

  • Cloud-first: Modern data stack tools are highly scalable and elastic and have become simple for organizations to integrate into their cloud infrastructure.
  • Developed around data warehouses and data lakes: To enhance data analytics capabilities, modern data stacks are developed around data warehouses and data lakes. To fully utilize the capabilities of all the well-known cloud data warehouses, they are built to integrate with them seamlessly.
  • Concentrate on resolving a specific problem: A collection of technologies connected by the various steps of the data pipeline constitutes the modern data stack that is leveraged for data processing and management of data.
  • SaaS and Open Core Offering: Mostly offered as SaaS (Software as a Service), sometimes, modern data stacks are also available as open-core, where components are open source. They are sometimes available with features such as end-to-end hosting and professional support, which are paid features.
  • Economical: Standardized pay-as-you-go and usage-based pricing models are available for modern data stack products. Before making major investments, data practitioners can investigate new tools’ capabilities and utility that help to save time and money.
  • Supportive Ecosystem: Time and effort invested by modern data stack solution providers in community building are high, which encourages a positive and innovative ecosystem around modern data stacks. This ecosystem consists of slack groups, meetups, and conferences that help data practitioners and those who leverage the tools.

How a Modern Data Stack is Beneficial?

Modern data stacks are beneficial for organizations in several ways. The major ways in which it helps organizations include:

  • Reduced Cost – While compared with on-premises clouds, modern data stacks are affordable for users, as the cost of cloud computing and storage is low. The cloud-based data warehouses only charge according to what we use, enabling to expand the storage as per our use.
  • Saves time – Traditional data warehouses take a lot of time for data processing, while data processing can be done within minutes using modern data stacks. The self-containment nature enables modern data stacks to enhance and configure simply.
  • Modularity – Teams can change out components of a Modern Data Stack as needed since it is composed of technologies with largely common connection points. As a result, organizations can increase their stack as their data demands develop and avoid vendor lock-in.

The time, money, and effort saved using a modern data stack will benefit the organization in several ways. The data value can be maximized, and the organization can develop insights through proper analysis of the data.

Conclusion

The efficiency and accuracy provided by modern data stacks have helped data practitioners and organizations to a large extent. Modern data stacks have enabled teams ready and eager to consider ways of resolving more complicated data challenges. The environment has been made more favorable for continuing innovation by new approaches like Data Operationalization, Stream Processing, Headless BI, and Data Mesh. The current data stack encompasses everything, from highly modular data stack components that enable gaining insight very quickly to lowering the technological barrier and providing enormous value for businesses.