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Why is Quality Data crucial for Business?

Businesses generate massive amounts of data from numerous sources daily at a frenetic pace. This means that the potential of this data is lost if we don’t know how to use it and turn it into accurate and reliable data.

High-quality data is key to making more effective business decisions and significantly impacts a company’s success. This is why companies should prioritize a data-driven business strategy. We tell you where companies stand today and how to change the prevailing view.

Why companies are not using data to make commercial decisions?

Despite the importance of data in the business environment, the majority of business leaders globally do not use data to make strategic decisions, according to Salesforce’s Untapped Data Research survey.

Nearly 67% of the 10,000 business leaders surveyed do not use data to set, for example, prices in line with economic conditions such as inflation. Only 29% use a data strategy when launching products or services in new markets, and only 17% achieve their sustainability goals.

Despite the data, 80% of leaders realize that data is fundamental to decision-making and can help drive greater efficiency and trust in their organizations if harnessed correctly.

Dangers of using low-quality or biased data

When data quality is poor, data-driven business decisions can lead to biased results. For example, it is crucial for a marketing campaign to consider all variables of potential customers to reach the right audience in the right way.

In fact, relying on poor-quality data to make important decisions can lead to costly mistakes that far outweigh the cost of investing in quality data in the first place.

Picture about big data and insurance

Many companies use raw location data. At first glance, it is less expensive than processed data, and there is more to work with, but it is often very problematic, as it is riddled with fraudulent devices or signals. Therefore, they would eventually have to be processed and cleaned, removing about half of the data. Without this step, companies have to deal with almost twice as much data, much of which does not add any value.

Best Practices to ensure Data Quality

As mentioned above, achieving high data quality is critical to making accurate and informed business decisions. We have therefore followed Forbes’ list of tips on how to put it into practice:

  • Determine the use case: One of the most important points is to define the business problem and the prospects you are trying to achieve. This will make it easier to identify which data you need and which are relevant to your needs.
  • Use reliable data sources: Choosing sources with a good reputation and a track record of high-quality and accurate data is very important.
  • Clean and validate data: This process involves removing or correcting any incorrect, incomplete, or irrelevant data, as well as verifying its accuracy and relevance.
  • Monitor data quality: this is a recurring task of periodically auditing your data to check for errors and assess the accuracy and relevance of your data.

By leveraging quality data, you’ll be able to make informed decisions, identify new opportunities and stay ahead of the competition – whether it’s optimizing marketing campaigns or improving business operations.

Data-Driven Strategy

So is it worth adopting a data-driven business strategy? The initial answer to the question is yes, as companies harness data’s power well and intelligently enjoy 3x higher revenues.

Data intelligence helps organizations create new customer experiences, accelerate operations and capitalize on new market opportunities. In fact, it also gives them the agility to pivot when the unexpected happens.

Of course, adopting an enterprise-wide data culture can be challenging at first, but it’s a great bet for creating corporate value at every stage and in every process. Executing such a strategy requires aggregating data and expanding access across the enterprise so that analytics expose broader insights and trends, but it’s not always easy.

picture about comparing data warehouse, data lake y data mesh

A Data Lake is one of the best solutions for companies that want to help break down data silos and use it as the foundation for an intelligent data ecosystem. Combining the ability of a Data Lake to store data in any format with the performance, security, and governance strengths of a traditional data warehouse is a highly recommended option if you want to change your strategy.

It will allow you to run a wide variety of analytics to improve decision-making, from dashboards and visualizations to real-time analytics and Machine Learning-driven capabilities. In fact, it’s becoming a competitive requirement in the digital economy, which is marking out which companies excel at making better business decisions.

Top Big Data Consulting/Services Provider 2023

To highlight the work in implementing these data strategies, the prestigious magazine CIOReview prepares a list of the best Big Data service providers each year, and Plain Concepts has been chosen as one of the best companies to enter this ranking.

One of the reasons was the generation of a value chain in our customers’ data with the help of cloud computing, AI, or ML. We transform data into useful information that helps them to build a strong data culture and evolve their business.

We aim to optimize all business phases, from customized platforms to data warehouses, enabling our clients to utilize the insights gained from data and improve their productivity and processes.

You can read the full article here.


And if you need to turn your data strategy around, don’t hesitate to contact us.

Elena Canorea
Elena Canorea
Communications Lead