Building a Mature Data Infrastructure to Accelerate Data Usability

Building a Mature Data Infrastructure to Accelerate Data Usability
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Modern technologies are being used to power data infrastructure with the perfect tools

Data is the major factor that drives strategic decisions in businesses, economies, and sometimes, even countries. Henceforth, delivering the right data in the right form plays a pivotal role in every sector. This has accelerated the need for data infrastructure that provides valuable information and insightful data for digital transformation. Besides, modern technologies are also used to power data infrastructure with the perfect tools.

Data infrastructure is an umbrella term that covers the process of data storing, maintaining, organizing, and distributing in the form of insightful information. It includes the data properties, the organization responsible for its operation and maintenance, and policies and guides that describe how to manage and make the most use of the data. By forming a good data infrastructure, organizations can drive valuable and high-quality insights to reach accurate decisions. Fortunately, the concept of obtaining the right data that drive digital transformation gained its pace in 2020. When people were busy moving to digital forms of working, they realized that they need to go on the right path and take the right steps before diving into a digital working mode. One of the major things that hit them was data democratization.

Many companies build products to manage and analyze data and they are fundamentally analytic systems that power data infrastructure to collect the data and display the analyzed results. The 2020 McKinsey Global Survey on the State of Artificial Intelligence reported that 50% of businesses have adopted artificial intelligence in at least one business function, and 22% of organizations attribute at least 5% of earnings before interest and tax to artificial intelligence initiatives. Since embracing technology with the help of data has become a trend, data infrastructure is seeking improvement by including other disruptive tools that could power the working system.

How to build a robust data infrastructure

To make data easily accessible, data democratization is very important. Data democratization comes with good data infrastructure. Henceforth, let's take you through the steps that help build robust data accessibility and processing.

Gather clean data: Collecting clean, right, and good data is vital for a professional infrastructure. For example, if your marketing team is gathering data on market statistics, you can get an overview of where your product is selling the most and where it needs more effort. If the strategy doesn't work, then you need to re-do your data processing again.

Choose your goal: If you start running vaguely towards data with the aim to develop your business, it is not going to lead you anywhere. First, set a goal, know what you want and what needs to be done in order to help you achieve it. If you collect data based on that, then it'll drive success.

Set up a data warehouse: The best way to get the maximum out of data is by setting a data warehouse. Companies can have two data warehouses to support their daily functionalities. One with clean and processed data that projects a better view of the actions and the other, unprocessed that needs attention when needed.

Ensure data security: Data security plays a pivotal role in its accessibility. Henceforth, organizations should ensure to customers that the data they collected is safe. In order to do that, they should regularly audit the data to strike out the ambiguities.

Mature data infrastructure use disruptive applications

As the importance of data infrastructure has spearheaded over years, we are now starting to see the rise of massive, complex systems built around data, where the primary business value of the system comes from the analysis of data, rather than software directly. Fortunately, companies are using disruptive technologies to make better use of data. Some of the innovative initiatives are listed as follows.

Cloud computing

In 2020, cloud computing has finally gained the recognition it deserved. Even though the concept was around for a long time, it got adopted and streamlined in everyday working only when people switched to digital transformation. In a wake to house data infrastructure, cloud computing is also offering numerous user-friendly products for collecting, ingesting, transforming, storing, and creating insights from data.

Data analytics

Gartner has highlighted that data and data analytics are the blueprints of digital transformation. The leading global organizations use data and its subsequent analysis as competitive weapons, operational accelerants, and innovation catalysts. Henceforth, new data analytics capabilities are emerging to necessitate the creation of new toolsets and infrastructure to implement these unique data and information requirements.

Data governance

While companies are busy collecting data and processing it, they often forget the fact that creating trust in data is essential for driving data democratization. This is where data governance makes its debut to ensure quality, consistency, and relevance. Recently, data governance platforms are merging to serve the purpose by offering tools that manage the availability, consistency, and integrity of data.

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