Big data ≠ BI business intelligence, and big data is not a simple upgrade of traditional business intelligence.
1. The difference between big data and BI
BI (Business Intelligence) is business intelligence, which is a complete set of solutions for enterprise data management. It is used to effectively integrate existing data in the enterprise, provide reports quickly and accurately, and propose decision-making basis to help enterprises make wise decisions. Business operation decision-making solves the problem of management and operation strategy.
Big data refers to the collection of data that is captured, managed and processed with conventional software tools within an affordable time frame. It requires new processing modes to have stronger decision-making, insight and process optimization capabilities Adapt to massive, high growth rate and diverse information assets. Big data focuses on methods to solve a certain type of problems, such as user portraits on the entire network, and analysis of unstructured massive data such as networks and sensors.
No matter how the definition is different, big data and traditional BI are the products of different stages of social development. Big data has both inheritance and development for traditional BI. From the perspective of "Tao", the difference between BI and big data is that the former is more inclined to Decision-making, the description of facts is more based on the commonality of the group, which helps decision-makers grasp the macro-statistical trend, and is suitable for the support of business and operation indicators.
Of course, purely from an ideological point of view, the two can be unified conceptually, and both follow the context of data-information-knowledge-wisdom, and even at a higher level, the two can be unified.
2. What is the technical relationship between the two?
Technical labels of traditional BI: ETL, data warehouse, OLAP, visual report.
Big data technical labels: Hadoop, MPP, HDFS, MapReduce, stream processing, etc.
At present, the functions of traditional BI can be replaced by corresponding big data components, but most enterprises lack the driving force of big data business and related high-tech talents.
However, the new BI is endowed with more "big data" potential. As shown in the architecture on the right side of the figure, BI is built at the big data application layer, and the data extracted from etl or Hive can be used for general business analysis. It satisfies both massive real-time data analysis and decision-making business analysis.
3. Should enterprises favor big data or business intelligence?
In the technical field, although some traditional BI technologies such as ETL, data warehouse, OLAP, and visual reports seem to be on the verge of falling behind, because it is difficult to solve the problem of massive data processing in the future, it cannot be completely denied or replaced by big data. Some enterprises use SAP HANA, and FineBI's direct-connected big data engine is an optimized solution based on this problem. The BI set will also exist for a long time. After all, enterprises still favor BI solutions, and the popularization and application of big data is also a long process.
Big Data vs Business Intelligence
Big data is not an empty talk. Its first priority is to solve business problems. To a certain extent, big data is to use new data technology to expand and optimize business. Traditional enterprises need to gather a group of people to study this problem, and special people are needed. Research and explore. If you think about the new business model externally, if you think about the scenario internally, you can use big data to improve efficiency.
At present, where big data can generate value, from the perspective of the industry, finance, banking, Internet, medical care, and scientific research all have broad prospects. From a field perspective, advertising, marketing, risk control, and supply chain are all places where big data plays a role. For specific companies, such as telecom operators, big data can also provide new methods for network optimization.
Not every enterprise needs to build its own big data platform. It needs to take into account the informatization level and various costs of the enterprise. Do what you can. You can develop it yourself, such as BAT; you can also select and purchase, such as traditional large enterprises; Small and medium-sized enterprises can also rent, such as Alibaba Cloud and AWS.
In fact, the application of BI is far greater than the application of big data, and there are general reasons for it. Compared with traditional BI, big data is not just a simple PLUS relationship. It involves deep changes in ideas, tools and personnel. BI personnel don't mention big data, but they sneer and think it is a newly packaged vest. In fact, that's the case; there is no need to belittle yourself, thinking that it is so high to engage in big data, it is indeed the inheritance of most of BI's ideas.