An article entitled “Analytics 3.0” explains the third generation in intelligent technology. It has been through two phases. These articles include both before and after big data. This third innovation in intelligent data should provide an integrated solution that allows for the use of large amounts of data to analyze performance, products, and services of any business. Analytical is now a key part of the strategy. This transformation requires companies to be able to identify new problems and then respond using enhanced functions and visibility (Davenport 2013). New datasets and administrative options will make the 3.0 version more robust. It also requires modified analytics, new systems, technology, and improved analytics. Third slide in lecture notes shows how analytics are used in sports. Slide 8 contains comments that confirm what the article says about the changing corporate climate. Analytics will evolve to include greater data processing capabilities and collaboration, as well as software and hardware upgrades.
This article examines the development of data analytics, from the first era through the third generation. Organizations were less efficient in the first era due to better data gathering. Big data dominated the second era and required more accurate evaluation techniques. Analytics is now in the 3.0 age. All businesses have access to data. This author discusses the enhancement of Beta’s capabilities. Davenport (2013) points out that Schneider Electric and Bosch have successfully embraced 3.0 analysis to fulfill their customers’ demands. Davenport also discusses what are the requirements for 3.0 analytics. This new technology allows firms to combine multiple forms of data. Schneider uses sensors to track logistical factors like fuel availability and location. Analytics 3.0 incorporates both modern and old methods for superior management.
These are the most significant lessons from this article. They focus on the importance of technology and how it is evolving. This article focuses on the need to ensure that enterprises are constantly looking for ways to evaluate their data and provide value. Many activities will be boosted by technology, which will continue to improve. Davenport (2013) shows the impact of analytics and technology on frontline staff.
Next, the article explains that companies should train their employees to be open to change. Davenport (2013) said that analytics 2.0 and 2.0 provided too much data on worker movements. However, analytics 3.0 will not provide enough information for employees to feel comfortable. Worker’s perceptions of change are well-known. Particularly in light of technological advancement, it is important to prepare employees.
Third, technology can enhance the company’s functioning. Here are some examples of companies that use analytics to increase productivity. No matter the type of business they work in, technology has been a way to increase productivity. Analytics usage has expanded to encompass all types of business, not just data and internet companies. Companies can take advantage of technological developments through continuous technological progress.