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Not sure what a Modern Data Stack Is? No problem! Visit our previous post where we explain what a data stack is, what a Modern Data Stack is, and the differences between them.
All caught up? Let’s dive right into the 5 Game-changing benefits Of implementing a Modern Data Stack.
Modern Data Stack tools mitigate the issue of vendor lock-in, as they’re designed to integrate with a greater variety of tools instead of a specific vendor ecosystem. They can be swapped out for different tools that although provide similar uses might be a better fit for the specific goals of a company.
Modern Data Stacks are cloud-based, enabling them to scale as needed to accommodate any surge in data volume, velocity, or needs without the associated costs or downtimes involved when scaling Legacy Servers and licenses. Cloud-based stacks avoid up-front payments with pay-as-you-go models designed around facilitating scalability.
Modern Cloud-based Data Stacks benefit from savings and cost reductions due to declining computing and storage costs, the possibility of re-allocating human resources by avoiding manual processing, and pay-as-you-go infrastructure solutions with no downtime.
The lack of a centralized data source where any analyst or user can cross-check data leads to users creating custom processes to do so. These processes might not be correct and may produce poor data quality, contradictory results, or inaccurate or unmatched data between teams.
A Modern Data Stack can join multiple data sources into a Single Source of Truth (SSOT), implemented as your Data Warehouse. This means metrics will be the same across tools and the organization.
Modern Data Stacks facilitate understanding of ownership, domain, and data flow. This is what Data Governance is all about: managing your data and avoiding chaos.
Furthermore, processes should be as clear as possible: Who do I have to ask permission for to access a certain asset? If there is no clear process to do this, a person might get unnecessarily blocked for a long period of time.
Data Monitoring adds an extra layer of understanding to your system: Which process is running that incredibly compute-intensive query? Can it be optimized? Else, should it run at a different time? Is it a critical part of the data landscape?
Modern Data Stack tools facilitate the process of understanding the impact your data has, where it comes from, its quality, who is accessing it, etc.
Stay tuned for further posts and whitepapers where we will get into Data Quality, Data Governance, Discoverability, and Observability, as well as the tools we recommend for these components.
Many tools that make up a Modern Data Stack are accessibility focused. For certain parts of the stack, usually associated with reporting and analytics, little to no code is needed. The technical know-how required to access data by final business users (marketing, sales, etc.) is reduced, enabling them to easily and routinely consult data to generate insights.
The possibilities for integrating Business Intelligence, marketing, or sales tools are endless. Furthermore, modern data stacks reduce time-to-market, or in this case, time-to-report drastically.
Read about all these benefits in detail in our brand new whitepaper on the Modern Data Stack where we cover:
You can also get familiar with the Modern Data Stack through our blog posts and case studies:
Mutt Data can help you crystallize your data strategy through the design and implementation of technical capabilities and best practices. We study your company’s business goals to understand what has to change so we can help you accomplish it through a robust technical strategy with a clear roadmap and set of milestones. Talk to one of our sales reps at firstname.lastname@example.org or check out our sales booklet and blog.