According to the definition given by the analysis agency Gartner, big data is the information assets with large scale, fast speed and three kinds of characteristics. Filter out useful information from massive data, and then turn information into insights through a variety of means to make the right decisions and ultimately drive business growth. Activate new ideas in data management to promote new models for enterprises Through a series of processes, Big Data can help companies develop sensible and practical strategies, gain unprecedented customer insights, support customer buying behavior, and build new business models to gain a competitive advantage. However, practice tends to be more difficult than theory. To deal with every aspect of the big data lifecycle, companies must adopt innovative and cost-effective processing methods and jump out of traditional data management thinking. What is the big data that brings value to the business? Consulting giant McKinsey once said that big data is becoming the frontier of the next generation's competitiveness, productivity and innovation, and it will bring great value to the development of the enterprise. But in reality, many business managers blindly collect data and analyze it, expecting to get a quick return. Unfortunately, they failed to do so. Regardless of overall planning, technology platforms, or business processes, most companies do not make special adjustments and changes to big data analytics. Traditional data management systems are preventing companies from extracting value from big data. First, business managers need to ask themselves the question: "How can big data help my business achieve development?" If you can't guide the action, then collecting more data is meaningless. In fact, gaining insight is one aspect, and practicality is one of the hallmarks of analysis. Is the company able to obtain realistic forecasts and forward-looking decisions from the “noise†of a large amount of historical data? Second, companies need to change traditional business processes and decision-making processes for big data analytics. According to traditional business management methods, high-level subjective opinions will have a decisive influence on decision-making, and this phenomenon is still very common nowadays. Let the real data speak, this is the conceptual shift that many business managers need to make. Of course, collecting more data doesn't mean turning data into insight. If there isn't a technology architecture that is more adaptive to the big data era, it will make the transformation of the enterprise even more difficult. Third, the technology platform is not a panacea, but no technology platform is impossible. In many cases, we will see the role of various perspectives in weakening technology. In fact, this view is one-sided. To truly harness big data, we still need a strong technology platform to support it. It's hard to imagine using existing SQL databases to analyze massive amounts of unstructured information. Big data requires us to have a more comprehensive and efficient platform for organizing, processing, and analyzing data. At the same time, you need to consider how to best integrate the big data platform with the original data architecture. New Ideas in the Age of Big Data: How to Realize Data Management Closed Loop To achieve these goals, SAP has summarized a methodology that can help companies think about the following issues and increase the amount of data that translates into real benefits: 1. Do I have the data I need now? 2. Can I get this data? 3. How do I mine the value of this data after getting the data? 4. How do I process this data when the business environment changes? When enterprises are transforming data management methods, they need to grasp and cover the whole life cycle of data from four aspects, namely, conceive, create, deploy and expand, and form an organic closed loop. According to this methodology, SAP has launched targeted big data services to help companies gain new insights from data, further expand business functions, and gain more business opportunities. In the envisioning phase, companies need to develop a big data strategy, roadmap and plan. Imagine the direction of the business and determine how big data will help companies target their business goals. At this stage, SAP's data scientists will help companies mine potential scenarios for big data, build business cases and determine what value big data will bring to your business. Once you have a roadmap and strategy in place, you can use SAP Big Data Services to create an optimal architecture that supports big data to achieve your goals. This process includes: securely integrating emerging technologies with existing investments; designing a comprehensive infrastructure to capture data from multiple data sources (usually existing data sets); implementing best big data platforms; and bringing big data to Impacts are included in the governance policy. In the deployment phase, it will also be the stage in which companies get rewards from big data. Through the big data platform, SAP Big Data Analysis Service and Application Implementation Service can support enterprises to run analysis applications, allowing enterprises to further control the overall situation and analyze current and historical information. Improve business outcomes with predictive analytics; communicate and share insights with great visualization; deliver information to business users as needed, and support information sharing on mobile devices. Finally, based on the company's existing big data potential, SAP Big Data Services will enable enterprises to deploy solutions in the most flexible, lowest-cost, and most demanding way to take advantage of the new environment and get richer services. Results. Deploy the solution through on-premises, cloud mode, or hybrid mode. Evaluate the company's existing capabilities, then build a competency center that delivers the new skills your business needs to manage big data more effectively and extend the reach of big data. From evaluating big data businesses to discovering big data values, designing big data architectures, implementing big data platforms, tools, and managing and optimizing big data solutions. In addition to the "all-round" in-memory data platform such as HANA, SAP can provide enterprises with an end-to-end big data service portfolio. Provide personalized guidance for companies in the transformation of the big data era, so as to take advantage of the various data sources of different processes to gain new and meaningful insights. to sum up On the basis of fully recognizing the importance of big data, companies need to understand the value points of big data to the business, and then make full use of data at every stage of the planning and every level of the enterprise to further expand the influence of big data. Form a virtuous circle. Let more employees, more regularly, make better use of those manageable data, and then let the business gradually take action based on the data. Through this new management thinking, I can really make big data work for me. Brushless Dc Driver,Brushless Dc Motor Driver,3 Phase Bldc Driver,Brushless Dc Servo Driver 3Kw Jinan Keya Electron Science And Technology Co., Ltd. , https://www.keyaservo.com