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Big Data Analytics Its Impact On Digital Transformation

Big Data Analytics: The concept of Big Data is already a reality in several companies, transforming the analysis carried out into spreadsheets and straightforward tables that are increasingly old-fashioned.

Aligned with the idea of Advanced Analytics, Big  Data Analytics allows the business to transform data into information for strategic decision-making through high-performance software or applications. 

By using this type of technology, the entire digital transformation of the company can be directly impacted and taken to a new level, with practical applications in various sectors such as HR, Supply Chain, and even the Marketing area. Professionals in these areas must obtain valuable and reliable information on the progress of processes and business indicators. 

The evolution of Big Data ranges from efficient data collection to its integration with the most diverse corporate bases and information sources. Keep following our publication and learn more about how this technology can directly impact the digital transformation of your business! 

The Concept Of Big Data And Its Evolution Together With Analytics

Big Data is familiar to most companies; attention to the stored data and travels through the services offered and consumed by the business adds more information and improves decision-making. This technology has the necessary potential to transform several sectors such as scientific research, administration, financial and operational areas. 

A significant evolution of Big Data was the integration with the concept of Analytics, allowing Big Data Analytics to become the standard in industries concerned with the volume and collection of data in a structured way. Promoting best practices for managing business data can also improve business practices by improving strategic decisions. 

In this way, executives and the management body can receive valuable insights that will direct the business toward the best trends in the market. And today’s scalable data storage capabilities offer few limitations to the volume of data that can be processed, enabling real-time analytics scenarios and applications that lead to better business performance from the insights generated with Big Data Analytics. 

Big Data Analytics Important Steps

Data collection is one of the first steps and must have a specific objective as a central point to be worked on to maintain the focus when generating insights. Different areas of the company may have different directions, and the storage and collection of data may be intended for future applications. 

After efficiently collecting data, data cleaning is a pre-processing of these data to generate a correct analysis of possible failures or anomalies. In inspecting the collected data, some statistical methods or even transformation processes can be used for removal and treatment. 

Content analysis and data mining can occur jointly or separately, depending on the type of Big Data architecture and the company’s maturity level. Data processing to identify patterns can use advanced techniques such as machine learning or search for relevant answers to the business – such as the profile of each consumer or a possible bottleneck during the production process. 

Visualizing information is also an important step. Constructing dashboards and tools that transform this information for straightforward interpretation is a significant step to demonstrating the power of data to decision-makers. Graphic adaptations and understanding the target audience that will use that information are great ways to deliver value to the analysis performed. 

Another critical point is integrating analyzed and processed data with other data sources – whether corporate or external – so that Big Data Analytics does not occur promptly. Blending into the management and command chain is a great way to maintain information quality and deliver true convergence between different technologies.

The Impact Of Big Data Analytics On The Digital Transformation Of Your Business

Big Data Analytics is applied for business optimization and positively impacts the company’s digital transformation as a whole. Promoting a better organization of data and the generation of insights offers benefits in the most diverse areas. 

  • Decision-making is one of the focuses of Big Data Analytics optimization, allowing the company to become more assertive and promote a culture of strategic vision based on data. Visualizing trends and customer needs is a great way to demonstrate the power of this technology. 
  • Identifying patterns can help identify your customers’ public and consumption profiles, in addition to promoting better integration of areas such as marketing and operations. Corporate data is also a great way to identify internal patterns and help identify bottlenecks and gaps. 
  • And thanks to this analysis and identification, optimizing the company’s internal processes can be a great way to internalize the benefits of Big Data Analytics. 

Big Data Analytics In HR

Modern HR must worry beyond bureaucratic processes, and Big Data Analytics can help improve the results of this sector. One of the first examples is the search for candidates in line with the profile of a vacancy or position within the company. The HR data analysis helps when looking for essential characteristics of external professionals. Big Data Analytics can previously select a group of candidates with the requirements, facilitating the task. 

Another task of the HR sector and people management within the company that can be helped using Big Data Analytics is performance evaluation and identification of potential leaders. Business information is an essential tool to understand the profile of each employee. 

Big Data Analytics In Logistics

Logistics also benefits from applying Big Data Analytics technology since improving operational decision-making in the supply chain is a great way to optimize cost reduction and increase efficiency. The data directly linked to the process and data from the devices and sensors that make up the business logistics can generate meaningful information. 

GPS data, presence sensors, tags, and even RFID guarantee essential information without having human interaction for the collection to take place – the sensors can be directly connected with the company’s Big Data architecture. 

Big Data Analytics In Marketing

The Marketing area can also benefit enormously from applying Big Data Analytics techniques, as it can build consumption profiles with incredible accuracy based on the historical data of its customers. They can also help forecast demand and discover new trends in the consumer market.

Also Read: How Big Data Can Contribute To Project Management

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