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What is the Modern Data Stack?
The right data stack should take your Business Intelligence to new heights – but how do you build one? Specifically, which tool or tools should you choose and, most importantly, can last-gen solutions solve today’s Business Intelligence problems?
In this article, we’re looking at what makes a “modern” data stack and how to build one with cloud-enabled data visualization platforms from providers like Astrato. Read on to learn more and discover ways to access modern analytics tools today.
What makes a data stack “modern”?
A “tech” or “data” stack is a collection of tools that allow you to collect, store, process, and analyze data all in one. These days, data stacks are largely cloud-based, meaning you’ll store your data off-site in servers run and maintained by an external provider like AWS, Google or Microsoft.
From here, you’ll probably have additional software solutions that pull data from your cloud environment and process it in some way to analyze it and experience it. The aim of any tech stack is to create new efficiencies by enabling easier collaboration and supporting critical processes across your organization by providing relevant and timely information.
So far, we’ve discussed what a “tech” or “data stack” is but not what makes it modern. Cloud computing plays a critical role in the modern data stack because it provides a range of benefits over a legacy data stack that involves on-premises assets. These include:
1. Scalable data processing
Unlike a legacy data stack, a modern data stack can stretch or shrink with your needs at a moment’s notice. So, whether you’re executing exploratory analytics to test an idea or you’re running huge applications 24/7, your data stack should be able to cope no matter what.
That’s why replacing your traditional data stack with cloud-native solutions is so important. Otherwise, you’ll be stuck with a legacy data stack that can’t grow with your needs and may even leave customer data exposed to bad actors.
2. Easy data integration
The modern data stack should also offer limitless data integrations via a composable or “modular” architecture. This is where your apps or software work together as part of a wider system without relying on each other too much.
Composable data integration allows you to replace individual components for more effective solutions or remove parts entirely without affecting the rest of your data platform. In turn, you can deploy the latest solutions within your data stack and stay up to date easily.
3. Intuitive and easy to use
Finally, a modern data stack should be accessible to all users regardless of their technical expertise as this will allow them to perform their roles more effectively.
Data literacy and accessibility are immensely important for any business. As such, it’s essential to look for data solutions with lots of integrations, so you can provide employees with relevant Business Intelligence in commonly used business apps.
Other factors to consider
Recently, there have been lots of exciting developments in machine learning tech. Generative AI software has the potential to revolutionize your analytics capabilities. So, it might be a good idea to consider where machine learning might be relevant in your business. Early adoption can help you secure a competitive advantage, as it’s only a matter of time before machine learning in the workplace goes mainstream.
Similarly, strong data governance practices are vital in today’s business environment. IBM data shows that the average data breach cost $4.35 million in 2022, which was a 3% increase since 2021 and a 17-year high. That’s why you should turn to cloud-based solutions so your data, and the insights you derive from it, are safe from bad actors.
Benefits of a modern data stack
1. Version management
A modern data stack gives you full control over your analytics by allowing you to test new ideas within your dashboards and revert to older versions easily if they’re not fruitful (or if something stops working). Similarly, you can see how your dashboards change with each modification, allowing you to customize your data stack to your needs.
2. Reusable data pipelines
Today’s data stacks let you draw from a bank of previously created assets, such as templates from your software provider or custom files built by colleagues. This makes it easy to build, deploy and test new analytics dashboards or data apps based on what’s worked best elsewhere in your organization.
3. Automated data processing
Modern data stacks allow you to run your business more efficiently by operating at a greater scale and completing tasks in a shorter amount of time. For example, you can find ways to free up your staff by automating certain tasks or analyzing large datasets faster than your current data stack.
Cutting-edge data stacks ensure users can share insights and updates easily, whether it’s via tagging them in files, creating shared workspaces or displaying updates within other apps in your tech stack
Why Astrato is a good addition to your data stack
Astrato is a no-or-pro-code data visualization and analytics solution, so it’s a highly flexible, and fully-customizable data platform. This means it can fit perfectly within your existing data stack to complement a traditional BI tool or function as the foundation of a new data stack.
As a cloud-native data platform, Astrato has seamless data integration capabilities. Astrato works with all the big cloud data warehouse platforms (like Dremio, Google Big Query, PostgreSQL, Snowflake, or Google Sheets). Equally, it can integrate with your existing legacy set up and on-premises servers, giving you lots of options when building a modern data stack.
Users can easily access analytics templates and data integration tools to share updates or build new data analysis dashboards in minutes. What’s more, our intuitive UI and no-code framework means it’s accessible to all users — from a highly seasoned data scientist to the average Business User.