Top 10 Factors to Consider When Building a Data Platform in 2024

In today's digitally inclined world, information has plainly come to assume an urgent part. Today, organizations produce humongous volumes of information, obtained from various sources such as website interactions, sensors, client exchanges, and so on. This information, thus, carries with it a wealth of opportunities for organizations to improve their decision-making, streamline operations, and gain an upper hand in the market. Sadly, realizing these advantages is far from simple or easy. First, to accomplish these benefits, organizations must lay out a vigorous foundation, i.e., a highly organized data platform that fills in as the central nervous system of the organization's data ecosystem. Such data platforms integrate data from different sources, ensure safe storage, and provide appropriate tools for working with said data. Hence, making a data platform is rendered a strategic decision that profoundly impacts a company's capacity to leverage its data for success.

So, folks, in this blog, I will discuss the 10 most crucial factors you should keep in mind when you engage a company offering services for data visualization consulting and start building your data platform.

What is a Data Platform?

A data platform is a collection of integrated technologies meant to help companies efficiently manage their data. It is basically a centralized hub for collecting, storing, processing, and analyzing data. Think of it as a command center for organizational data.

10 Vital Factors to Consider While Making a Data Platform

1.Understanding the company's data requirements: This process precisely defines the data you need to collect, store, and analyze to achieve the defined business goals. You must identify existing data-gathering practices, determine additional data source requirements, and define how the data will address business inquiries.

2.Financial considerations: Financial factors incorporate costs connected with technology, software licenses, infrastructure, and so on. It's important to account for not only initial setup costs but also continuous operational costs, upkeep, etc.

3.Security: Companies must define robust security protocols to protect their sensitive data, ensure data privacy, prevent unauthorized access, and other such security events.

4.Testing: Before a data platform is put to work, companies must thoroughly test key functionalities such as data ingestion, processing pipelines, etc. to see that all components of the platform operate as planned.

5.Scalability: Since scalability is necessary for managing increasing data volumes, it is advisable to choose a platform that can be horizontally scaled by adding more resources or vertically scaled by upgrading existing resources.

6.Integration: When developing a data platform, integration is what helps ensure smooth compatibility with current data sources, apps, and BI tools among other such things. So, analyze the platform's compatibility with the existing data ecosystem.

7.Compliance: Compliance helps ensure alignment with data privacy laws such as GDPR or CCPA. So, see to it that the company adopts data governance policies as well as procedures for responsible data management.

8.Support: Reliable technical support is also vital for addressing issues, managing platform updates, and ensuring smooth operations. So, before you find a technology provider, be sure to assess the quality of the support they provide.

9.Cost: When building a data platform, you must consider long-term costs and the initial investment.

10.User-friendly interface: Zeroing in on an intuitive design that makes the platform usable for users with varying degrees of tech proficiency is important. All things considered, a user-friendly interface can energize data democratization, allowing more individuals to successfully access and analyze data effectively.

Carefully considering the above-listed factors is a great way to build a data platform that can effectively meet your organization's needs.