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Get the Inside Scoop About Modern Data Stacking

Keeping a business running can be a difficult responsibility. When you consider the multitude of decisions and the magnitude of their impact on your enterprise, handling your data collection can seem like one chore too many.

How about having the equivalent of an assistant to organize and sort through your data?

Having an out-of-the-box modern data stack platform is the simplest way to consolidate, organize, and clean your data with the use of SQL and a few button clicks.

Here is a closer look at what the modern data stack looks like today.

What is a modern data stack?

From the perspective of platform developers, a modern data stack is all about using sophisticated technology that makes it possible for data analysts to swiftly consume data from various databases and SaaS tools and decipher it.

This set of technologies that enables a true data pipeline is about going beyond reporting data findings but getting to the point that value is being derived from the data.

This data stack involves extracting data from siloed sources into a singular data warehouse, transforming that data so that it is accessible, clean, and consistent with what is needed for internal business use.

Then using tools in that data stack to patch that data warehouse into a business intelligence tool to purposefully visualize the data to strategically guide important business decisions.

More simply put, a modern data stack is a suite of tools used for data integration that help your data flow through the true data pipeline.

Let’s discuss the benefits that come with utilizing a modern data stack in your organization.

Modern Data Stack: Automate Your Data Integration

The core of the modern data stack (MDS) is a powerful cloud data platform, separating storage and computing with scalability.

Typically, the hub is a cloud warehouse, which can also include data lakes, and into that warehouse, data gets loaded from numerous source systems, such as APIs, databases, and web applications.

In order to make this happen, a reliable transformation layer is used to convert raw data into query-ready datasets.

A collaborative business intelligence and visualization solution enables the business to interact with the data and draw actionable insights to guide business choices.

The Modern Data Stack is able to blend cloud-based data sources with on-premises solutions that exist in businesses, whether big or small, to offer data professionals an automated way of keeping up with the business and supporting decision-makers with mission-critical and consistently up-to-date information.

Making Data Actionable

Taking action on data is really the next level of data warehousing to close the gaps that previously interrupted the fluidity of observing and retrieving data.

Look at it this way, instead of your data warehouse producing a bar chart and someone viewing that chart and taking action based on it, a machine is able to go directly from the insight gleaned from the results of the query to actually doing something with it.

Use cases include automating payroll and billing, monitoring intrusion detection, and detecting marketing problems that can save an organization millions of dollars.

The Modern Data Stack Will Shrink Latency Time

Having the ability to achieve lower latency time will be key to supporting these new use cases of the modern data stack.

Latency is the total time that it takes a data packet that is transmitted to return back to its source.

With that said, there is no such thing as latency that is too low, and with the new features that are being developed in the data warehouses, latencies of seconds and tens of seconds are fundamentally possible.

Data Engineering Overhead

A modern data stack can decrease your data engineering costs by at least 90% by getting rid of the need to build and maintain data pipelines or normalize data from denormalized APIs.

Prebuilt, fully managed data connectors launch in minutes and deliver ready-to-query data to your preferred data warehouse or destination. When it looked to improve its analytics by centralizing data, its first option was using in-house resources to bring data into its existing SQL Server warehouse.

On Premise vs. Cloud Data Warehouses

These new solutions fundamentally differ from simply on-premises warehouses recreated in the cloud, offering a better user experience and enhanced performance compared with legacy solutions.

If you are in the process of building a new system, cloud-based data warehouses that separate compute from storage are ideally the center of your modern data stack.

Those tools in the modern data stack allow you to have a clear awareness of how to proactively reach out to customers, better forecast what your company is selling, winning, or losing, and what marketing and sales channels are the most effective.

Identify your customer activity during sales changes to predict what the outcome is going to be prior to forming an unhealthy customer relationship.

Now that we have discussed many of the amazing advantages of having a modern data stack, now all you have to do next is get started.