What is the significance of digital transformation? This is the answer to the question that every enterprise is looking for, and the most common answer is the reinvention of business processes. This process may be painful, but the results brought about by digitalization are indeed fruitful.
Data analytics, an important technology for digital transformation, allows companies to win more superior business results. Whereas before, companies often needed to adjust their strategies only after encountering failures, now they can quickly gain insights through data analytics to guide business development and improve competitiveness.
Gaining insights from data analysis
Gartner expects enterprise IT budgets to increase by about 10% in 2017, with a significant increase in IT budgets spent on "digital".
Of course, the challenge of digital transformation for enterprises is huge, because it may redefine the enterprise, not only IT, but also includes processes, business models, employees and everything else. This also requires business managers to clearly align technology with business goals and make technology a business enabler.
In the process of digital transformation, the application of data analytics is of great significance to enterprises, which have changed from simply storing data to using data analytics to gain value, and through data analytics enterprises can gain business insights to guide decision-making and development.
Gartner's recent survey shows that business intelligence and analytics (BI/Analytics) has become the top IT investment concern for CIOs, followed by cloud computing and infrastructure.
However, there are many problems with the application of data analytics in enterprises. Teradata found that enterprises encounter three major challenges in the process of data application through communication with customers from various industries: first, business level, analyzing and improving in business scenarios; second, talent level, the pressure on talent resources is a problem faced by every enterprise; third, architecture level, the need to consider the high performance of the architecture, agility, scalability as well as cost and other factors.
In Teradata's view, big data applications are divided into three realms: "data, analysis, results", using analytical data to better enable business insights and help enterprises achieve a comprehensive digital transformation.
Discovering value from business scenarios
What enterprises want to see most in digital transformation is that data analytics can generate value in business scenarios and even create new business models.
Teradata's customer in Europe, Enedis, is a French power company that manages the maintenance, development and operation of 95% of France's distribution network as a neutral distribution system operator (DSO), with interests in nuclear, thermal, hydro and new energy generation.
Enedis has two main activities, firstly, managing the continuity and quality of service for 1.3M km of power lines and secondly, providing non-discriminatory access to the distribution network. As a power company Enedis also needs to guarantee the top priority of uninterrupted power, the company not only operates, maintains and develops the network, but also invests in digitalization and modernization for security.
Doing all of this Enedis relies entirely on the results of data analysis, with its smart meters and sensors generating large amounts of consumption and environmental data on the network, which is fed into analytical systems used to perform internal and external operations. One example is Enedis' combination of historical data from the past 10 years and multiple data sources, such as temperature, to understand the causes of transformer failures. Predictive maintenance is performed on equipment to improve reliability while ultimately increasing customer satisfaction.
This ability to gain insight is also exported to the supplier side, providing real-time insight into customer usage and the assets of the grid, allowing suppliers to determine grid connections, pricing, and even reduce non-technical losses.
Through data analysis Enedis also gives the end consumer more choices, which not only saves energy and money, but also increases customer satisfaction. In the future Enedis hopes to give customers better energy control and consumption models, including connected wind power, electric vehicles, and smart cities.