What is Data Socialization in Data Analytics?

If you are a data practitioner or business analyst, you may be familiar with the situation where you are grappling to respond to business demands. The endless circle of data access, data processing, and reconciliation, may be a challenge, especially when facing a dearth of time or staffing. You may be unable to find the necessary information and are ignorant about the many self-service data preparation tools available to make tasks easier.

Moreover, the 24/7 connected ecosystem has increased the expectations of users. They demand instant access and processing notwithstanding, where the data resides or the format.  They want the data for easy and instant sharing with their team members or stakeholders. This has emerged as one of the biggest challenges in data analytics.

The problem is solved with Data Socialization, the transformation of data access for self-service across individuals or teams. Data Socialization is the latest buzzword in data analytics and management, rewriting the way organizations think and interact with their business data.

So how do you prepare for Data Socialization? Register for the Data Analytics program to learn how you can benefit from the PG program in your chosen career in data analytics.

What is Data Socialization?

Data Socialization refers to the sharing of data and data analysis tools with members of an organization to ensure that data-driven insights are accessed by everyone.

In an always-connected world, the socialization of data connects data in a way that interacts with platforms and reshapes business and decision-making. It is a revolution in the emergence of data accessibility and self-serving analytics, facilitating a new way for organizations to interact with data.

The information created and processed by data scientists often gets lost as it transmits between departments, offices, stakeholders, and the teams working on the data. Information becomes messy and incomplete, making it difficult for scientists to evaluate and make sense of scattered pieces of information. This is where Data Socialisation develops a methodology wherein data and data analytics tools are shared and made available to all the team members in a company as and when required. Is it any wonder that Data Socialization has emerged as the mainstay of sharing corporate data?

Data Socialization involves a data management platform that facilitates self-service data preparation, data discovery, cataloging, automation, and governance, like social media platforms. It enables data scientists and business analysts to look for, use and reuse, share and collaborate with data, thus achieving agility and business response to events. Any employee permitted access to the data can find and use the data, thus facilitating a social network of certified and filtered raw data sets. Controls are established for each employee to manage and limit access to the type and range of data available.

This promotes a culture of data access and usage, with analysts learning data governance from one another to become more productive and connected as they source and prepare data for analytics. Companies also provide the facility of user ratings, discussions, and feedback mechanisms for better employee awareness and speedy decision-making. This supports enterprise agility and productivity.

Why is Data Socialization the next best thing in analytics?

Data Socialization reaps the benefits of self-service data preparation and analytics.  It removes the obstacles to data access and sharing. BI analysts, data scientists, and users are empowered and energized to work together on the data. The right person is given access to the right data at the right time. It enables millions of data points to be brought together under one umbrella and empowers the analysts to learn, communicate and share the data. Data can be curated and managed for data analytics tasks. This is why the implementation of Data Socialization is considered the next best thing in analytics.

Data Socialization helps businesses make the best use of their data, with minimum silos and time lost.

Businesses collect huge data that is often manually entered into IoT devices in various formats, structured and unstructured. Yet previously, the extent to which this business-critical data was accessed was only by a limited team of business analysts. Unless data analytics is a part of job responsibilities, an employee never had access to data; relying upon others working in data management roles to collect and analyze the data and provide suggestions based on it. It did not work, as there was over-reliance on a small group of analysts for the data access and processing, which posed a challenge. This is more so when the company handles big data. A small group of analysts cannot process the entire organization’s data or deliver insights to every department.

The need to access data is at an all-time high, with data forming the mainstay of many innovative products and services. With the development of cloud technology, employees have higher expectations of the data accessed by them. The increased availability of data and cloud services have enabled sharing across multiple people and business units easier, shaping data management processes and protocols for more data democracy. Thus, Data Socialization has enabled higher productivity, as users have the right data when they want it for analysis. By improving agility and performance, businesses have an advantage while competing in markets.

Besides, very often data analysts have limited knowledge of other departments of the organization, which limits their ability to implement data for other business units.

Data Socialization solves these challenges by placing data and analytical tools directly in the hands of team members who use them in their jobs.

Summary

Thus, Data Socialization has emerged as a way for businesses to handle analytics and big data. It empowers every employee in the organization tasked with the responsibility of analysis with the capability to manage and decode data.

As employees realize the immense benefits accruing from Data Socialization, companies are deploying Data Socialization practices and self-service tools for better productivity and efficiencies across the organization.

If you want to carve a career in data analytics, explore the realm of Data Socialization to understand data management and analytics best practices.