How does Big Data Facilitate Digital Transformation?

How does Big Data Facilitate Digital Transformation?

Firstly, ask yourself whether or not your organization is making the most out of big data’s power to increase digital transformation opportunities.

The term big data was used fifteen years ago to describe the increasingly large, diverse, and complicated volumes of data that are not easy to handle with the traditional data management approach. Most digital transformation efforts are based on large amounts of structured and unstructured data analysis to acquire insights in real-time since the knowledge gained through big data analytics is utilized to drive workflow digitization and automation.

Businesses attempt to make the best use of the massive amounts of data assets, which results in the emergence of digital transformation. According to Todd Wright from SAS, digital transformation focuses on transforming your organization to make its decisions on data. And big data can help capture all the available data an enterprise can generate or use. The big data collecting process is crucial to digital transformation efforts. IT businesses can undoubtedly use big data solely for reporting and process enhancement purposes. However, the real value comes from the capacity to connect big data with digital transformation efforts to facilitate digitization and automation of every business activity to achieve efficiencies and new business models. Prashant Kelker from ISG describes digital transformation as the path and big data as a means to reach there.

Big data to enable digital transformation opportunities:

Big data, at its best, can shed light on areas of the business that would otherwise be dark. These well-managed and massive amounts of data can provide you with a better understanding of operations, customers, and markets when integrated with analytics or an AI platform. The bottom line is that a large volume of data is required for digital transformation to be truly successful and achieve better insights for business goals.

Big data can be useless without the help of a well-thought-out idea or software to make use of it. Digital transformation also assists you with the concept and program. When it comes to whether or not big data is essential for digitization, the more information that gets into a program, the better the results.

Real change is possible when the two converge. The amount of data generated by IoT devices, wearables, smartphones, and other machine sensors expands exponentially as the number of them increases. The mixture of IoT data, big data analytics skills, and digital transformation helps companies respond to customer needs in real-time and forecast the future behavior of their consumers. Enterprises must build a modular but cohesive digital platform powered by big data gathered from different resources.

It helps them keep up with the growing proliferation of internet-connected devices, evolving data-driven digital business models, and increment in globally connected business ecosystems and integrated value chains. The business value (or return on investment) that an organization might receive from its digital capability platform investments can be determined by its data value extraction capabilities. The volume of data generated by prominent businesses is enormous, and it cannot be managed using typical business intelligence and data warehouse procedures.

Go for integration instead of isolation:

IT leaders can use digital technologies to extract the most value from big data to create data hubs for aggregating and staging data from various sources. Many big data providers offer IT leaders pre-built analytics and machine-learning algorithms. However, big data and digital transformation projects need to be defined clearly for the specific company and industry.

For example, an organization must first decide whether its goal is to boost revenue through connected products, reduce expenses through a more streamlined and connected shop floor, or a combination of the both. Only then will IT leaders decide on the ideal big data, IoT, and cloud strategy to meet those goals. To make the digital transformation happen, you should have a specific objective or target in mind. It could be new revenues, saving costs, or both. It helps define the path and guide you through the implementation of technology.

Too many big data efforts still begin with an IT or business intelligence department and then die out because of the lack of business value. When big data initiatives are implemented in isolation, they appear to be solutions in finding a problem to solve. Well-executed digital transformation provides the glide road for technology, including big data initiatives.

Big data and digital transformation can also assist businesses in understanding client preferences and behavior better so that they can provide more personalized and relevant experiences. The emergence of insight-based products and services allows for more than just pure monetization. Companies are also using big data to create new products and services that will help enhance the top line.

Take a proactive approach:

Big data efforts can also affect digital transformation, especially when the data is not backed up by a robust data governance program. Organizations can not access more data from more sources without metadata management, data quality, data catalogs, designated security, and data owners. IT leaders that are most successful in utilizing big data to promote digital transformation apply a proactive approach. They begin with a data management plan. A successful digital transformation needs to be based on reliable data.

Firms that invest in data governance, advanced analytics, and machine learning get various benefits from the big data-digital transformation combination. It can range from better operational efficiency to improved customer experiences to increased revenue. Supply chain digital transformation is an example of how the developing need for operational resilience led businesses to start their digital transformation journey. The essential element in this journey is to track the data about how materials, finished goods, and information assets are moving within the supply chain. Data insights can help businesses improve the efficiency of their whole value chain, including distribution, logistics, manufacturing, and sales. 

Therefore, it is clear that big data can help organizations gain control, make strategic decisions, improve efficiency, and provide complete customer satisfaction. Big data intervention and use should not be limited to the organizational level. Instead, each department should be able to access it to brainstorm a clear roadmap and identify precise business requirements both externally and internally.

Author’s Bio:

Deepali Daiya is a communication expert who excels in understanding customer needs. Currently, she is associated with Sage Software Solutions, a leading distributor of high-quality ERP Software and CRM systems to small and mid-sized businesses in India.

Technology