The need for data democratization in the digital enterprise


This article is written by featured blogger Naveen Joshi from his blog page. Republished with permission of the author.

The democratization of data enables individuals in organizations to access data without any bottleneck in making data-driven decisions. And it helps organizations move closer to their vision of becoming fully data-driven.

Digital businesses require a huge amount of data. This data helps them improve their performance and simplify their daily operations. But often data is only accessible to business leaders, managers and data analysts. But business leaders and data scientists typically may not know what information employees need. As a result, having access to data by only a few people across the organization prevents businesses from making optimal use of it. And this restriction prevents businesses from becoming complete data-driven organizations.

Data democratization refers to the fact that data is easily accessible to all employees of an organization without any barriers. The democratization of data can help businesses realize their vision of becoming data-driven.

The vision of data-driven organizations

Data is an essential part of every organization today as it can be used to improve business operations. Using all digital technologies, whether it’s AI, BI, or big data analytics, requires data entry to function effectively. The advantage for companies is that with IoT and big data, an abundance of data is easily accessible. And businesses want to use that data to make decisions. Indeed, data-driven decision making has various advantages. With data-driven decisions, businesses can make confident decisions, whether to develop marketing strategies or make infrastructure changes, based on the information generated. It can also help businesses become more proactive. For example, predictive analytics will help identify business opportunities ahead of a competitor. But, despite an urge to become data-driven, most organizations don’t even come close to achieving the vision. And that’s because of the hurdles they face in becoming a data-driven organization.

Barriers to vision

According to a survey, 31% of people say they have created a data-driven organization. The remaining 69% are very late in their journey towards the democratization of data. This is because most organizations only give access to data to business leaders, data analysts, or the IT department. These people may get information that is relevant to their job, but that information may not be useful to other employees. Depending on the function and hierarchical level of employees in an organization, they require different types of information. For example, a business owner may need information such as increasing or decreasing sales. A salesperson, on the other hand, may need information such as why sales have increased or decreased. Also, in the case of growth, they might want to know how to act to maintain it. And if there is a decline, they may want to gain actionable insights to increase sales.

Another obstacle that presents itself in the way is the scarcity of data analysts. Businesses want to mine every bit of data, but there aren’t many people with analytical skills. This has exponentially increased the demand for data scientists relative to their availability. And this growth in demand has led to an increase in the costs of hiring data analysts. Therefore, not all organizations can afford to hire a full team of data scientists to analyze every bit of data. This further led to a reduction in data information. By making data available and accessible to everyone in an organization, data democratization can help them overcome these barriers and become a data-driven organization.

The boost of data democratization

The democratization of data can be the stepping stone to help businesses overcome the hurdles to become a data-driven organization.

To compensate for the lack of data analysts

The demand for data scientists far exceeds their availability. According to a survey, the United States alone faces a shortage of 151,717 people with data science skills. The democratization of data allows each individual to access and analyze data for better decisions. And with each employee leveraging data for their benefits, data scientists can focus on more complex analyzes and generate deeper insights. The democratization of data will also allow large organizations to operate with a few data analysts. This will reduce the demand for data analysts and bring it closer to availability. Companies can also integrate NLP into their analysis tools to further simplify data interpretation. NLP will convert the information generated by the data into plain text. This will help employees understand complex data structures. In addition, they will be able to communicate with data in natural language and deepen their knowledge.

To provide information to employees

Since each department will have access to the data, they can understand the data and generate information according to their needs. By considering the same sales example mentioned above, the sales team will be able to gain actionable information to maintain and increase the number of sales. The democratization of data will also reduce the amount of dark data. Dark data is data collected by business systems but which remains unused. Business leaders might prefer to generate consumer-focused information. For example, they might want to know how to retain customers or improve their experience with the business. And that’s because they don’t have the time to focus more on other ideas. But, this results in an unknown bias. By focusing on consumer information, non-customer data such as networking data and log file data remains remote. And this increases the amount of dark data. Since each individual will have access to the data, they will generate consumer information themselves. And it will give business leaders time to not only focus on consumer data, but also to generate insight from dark data. For example, they can generate information from networking data to find out how they are using their resources. And this information can help them reduce costs or make the best use of Internet and network resources.

To improve real-time decision making

Often, employees have to rely on managers and team leaders for data-driven insight. And business leaders would generate information when they felt the need to. And on top of that, this information might not even be of much use to end users. With the democratization of data in place, employees would be able to generate information themselves.

The ability to access data at any time will help employees make real-time decisions based on the data. For example, retail sales employees can view the purchase history of all customers. With access to all historical data, employees will be able to provide real-time recommendations to customers. For example, if a customer recently purchased a shirt, employees might recommend jeans to them. This will improve the customer experience and make it more attractive. Real-time analytics will also help employees deliver promotions and incentives to consumers based on their loyalty to the store. Suppose a customer has been shopping at a retail store for over a year and has made purchases worth more than $ 500. Employees can offer them loyalty bonuses based on standard terms decided by owners and managers.

The democratization of data brings various benefits to companies like the ones mentioned above, but it comes with certain concerns. The democratization of data enables non-technical employees to understand data. But, there are always risks of misinterpretation by employees. And these misinterpretations can lead to bad decisions. Therefore, despite the simplicity that the democratization of data brings to understanding data, companies need to train their employees in how to interpret data. Companies can organize training sessions to educate their employees. They can also use AI to enable collaborative learning to help employees better understand how to interpret data.


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