4 Things to Look for in a Modern Data Platform

4 minute read
4 Things to Look for in a Modern Data Platform

Data-driven decisions require the ability to quickly and reliably analyze your data. How fast organizations can collect, process and analyze data can make the difference between who leads the market. Is your current data platform slowing you down?

Traditional data architecture can be too rigid, overly costly, complex and unable to bring together a wide variety of data types. With various tools and technologies stitched together to perform data integration, transformation, aggregation, etc., there are many points of failure in delivering data from its raw source to its intended destination. Many are simply unable to handle the explosion of data that has become available over the past few years.

4 key characteristics of a modern data platform

Learning about the different characteristics of a modern data platform and how modernizing your database technology can help you maintain a competitive edge for years to come.

1. The rise of cloud technology

Unlike traditional platforms that are built with hardware resources that are scarce and costly, cloud solutions offer unlimited capacity both for storing and processing data. This offers the ability to run an unprecedented number of workloads and analytics queries with high performance in a centralized platform. There is no need to purchase physical hardware.

This typically makes cloud data platforms less expensive because you can scale usage up and down automatically, compared to traditional data architecture where you pay for capacity whether you use it or not. You no longer have to anticipate storage, hardware, and software upgrade and capacity issues as you would with traditional technology.

2. Discoverable data

A modern data platform has the ability to manage many types of data—from structured to semi-structed—and from any source, whether it’s on-premises or cloud based. It also unites data that may be in disparate locations to reduce complexity.

Governance, security and silo issues are commonplace with traditional data architectures and, unfortunately, multiple copies of data eventually emerge to meet all the different and varying needs of your business. In the end, you spend more time managing infrastructure, and little time actually working with data.

This is the script we are trying to flip. Since you can easily scale up and down on the cloud, processing speed is no longer an issue, making it easy for you to quickly analyze and get insights from your data.

3. Democratization of data

Do you have to limit your data insights to a small group of users?

In today’s business world, everyone is an analyst on some level and there is a high demand for quick access to analytics across the business. It’s time to thoughtfully increase access.

By increasing the access to and usability of your organization’s data, you can:

  • Free up time for your data scientists
  • Eliminate clunky report request processes, and
  • Empower non-technical data professionals to answer their own questions

Modern platforms should be designed for self-service and understanding, eliminating long turnaround times so you can get important and accurate data into the right hands. 

4. Utilizing modern tools: artificial intelligence & machine learning

Using new technology such as artificial intelligence (AI) and machine learning (ML) can help you build a smart data platform with capabilities to automate processes and provide sophisticated analytics. A modern data platform can provide predictive analytics, which can offer insights into the forecasting you need to make better business decisions. By augmenting analytics with AI, your data platform will be able to spot trends and patterns you may not even think to look for.

The ideal data architecture should use deep learning techniques with ML and artificial intelligence that can be used to build data objects, tables, views and models. This architecture uses intelligence to identify data types, common keys and join paths, find and repair data quality errors, map tables, identify relationships, and make recommendations. A modern data architecture uses these techniques to learn, make adjustments, and provide helpful alerts so that those administering and using the environment are vastly more efficient and accurate.

Modernize your data strategy                                       

Building a modern data platform is important for businesses because it enables them to handle the volume, velocity and variety of data necessary to be on the cutting edge and ahead of competitors. It allows you to spend less time managing infrastructure so you can focus more on working with the data.

Ready to start exploring ways to modernize your data strategy, but not sure where to start? Working with an experienced solutions provider can help. Whether you need to harness the power of your existing solutions or implement new tools to get more AI-driven intelligence from your data, a solutions partner can help analyze your current ecosystem, build a roadmap, then execute your modernization strategy.

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