The integration of traditional and innovative big data solutions from IBM

Today, massive volumes of information are filled with the IT world. data shows that in the next decade, data and content around the world will increase by 44, 80% of which are unstructured data. The advent of the big data era brings challenges and opportunities to enterprises. How can enterprises quickly and effectively grasp valuable information and data when Big Data swept across the world? In the face of many big data and analysis products, many enterprises have begun to find a solution to big data. What is big data? According to Wikipedia's definition of big data, that is, a collection of data that cannot be crawled, managed, and processed by conventional software tools within a certain period of time. Gartner also raised three major challenges that big data brings to users: Variety type, Velocity speed, and Volume capacity ). Currently, users need to manage various data types and data structures, from traditional table data to emails, images, videos, social networks, and other information; speed indicates the speed at which dynamic data is quickly generated and processed. The speed requirement for data collection, processing, and use is the second challenge. When the data volume reaches the TB or PB level, traditional algorithms that process small amounts of data cannot process large datasets quickly and effectively enough. Both storage media and management analysis have been greatly challenged.Any single product cannot solve big data problemsThe advent of big data has become a top priority for enterprise development, and many IT giants have joined the ranks of big data to launch their own big data products, such as sap hana, Vertica acquired by HP, InfoSphere BigInsight of IBM, and Big Data Appliance of Oracle. Each Vendor's Big Data products have their own characteristics, however, can every product help enterprises comprehensively cope with big data problems? Zhu Hui, general manager of information management software at the IBM China R & D center, believes that "the big data problem needs a complete set of solutions to solve, any single product cannot completely solve the big data problems and challenges faced by users. It is necessary to integrate information management software, services, consulting and other products, and integrate traditional and innovative methods to solve the big data problem ."

General Manager of information management software at IBM China R & D center

Along with the emergence of big data, Hadoop has become a hot word attracting users in the IT industry. The growth of Hadoop has also been supported by many enterprises, almost all IT vendors have successively announced their Hadoop-based big data strategies. However, can Hadoop solve all big data problems? Zhu Hui believes that "Hadoop technology is more suitable for analyzing massive static data, but it cannot meet the needs of dynamic analysis. Big data products have no substitution relationship with traditional relational databases and data warehouses, but are complementary. In the future, traditional data warehouses and OLTP online processing will all be integrated into one platform ." According to reports, the vision of the IBM Big Data Platform is to provide users with a big data environment through the IBM Big Data Solutions and client and Partner solutions, multiple open-source components such as Hadoop, HBase, and Jaql will be integrated at the same time, integrates with IBM data Warehouse InfoSphere, Netezza Warehouse, InfoSphere MDM for master data management, DB2 for database, content analysis ECM, business analysis Cognos and SPSS, marketing Unica, and InfoSphere Optim for data growth management. software. IBM will discuss and develop platform solutions for solving big data problems with customers. Scarce Big Data Technical TalentsThe arrival of big data has brought infinite business opportunities to many enterprises. It is very important to understand and predict customers' preferences and market developments, master the core information content means that it will take the lead in the competition. Enterprises should seize this opportunity, but this requires support from technical personnel such as data analysis and predictive analysis. McKinsey's Global Research Institute predicts that in the next six years, only in the United States may face a shortage of 0.14 million to 0.19 million people with in-depth data analysis capabilities, at the same time, there is a gap of 1.5 million managers and analysts who analyze big data and make effective decisions for enterprises. In the face of many talent gaps, what strategies does IBM have to help enterprises cultivate and deliver relevant talents? Zhu Hui told reporters that IBM needs to work with its clients to learn and master big data talents. In terms of technology, IBM is based on its own solutions and platforms, vigorously cultivate big data solutions, including setting up courses and teaching materials in universities. According to IBM's "CIO-critical revelation of the global CIO survey", 83% of CIOs already have long-term plans covering business intelligence and analysis, and CIOs are starting to focus more on data, instead of applications. The ability to control big data is also related to the development of enterprises. This ability can help enterprises support business decisions. In the next few years, big data will gradually become part of the CIO's work.