Business intelligence upgrades in the big Data age

The BI (business Intelligence) system is a popular system for CIOs, because it allows CEOs to personally experience the value of information, and the growing popularity of mobile bi speeds up the use of business intelligence systems by CEOs. "Ufida Huabiao general manager Miao to reporters. As we all know, the source of BI is data, and the object of BI is data. According to IDC forecasts, from 2009 to 2020, the total amount of data will increase 44 times times, to reach 35ZB. Of these, 80% of the data is unstructured data. There is no doubt that, with the advent of the big data age, massive data has brought unprecedented pressure to BI.  How to make effective use of large data, as well as the information precipitated in the future, becomes a major competitive focus.





Consolidate all data





whether it is large interactive data or large transaction data, processing and analysis of unstructured data is a difficult problem in the bi industry.




Atul Patel, vice president of Business analysis and sustainable development,
SAP Asia Pacific and Japan, told reporters that the new 4EB data were produced in 2011. The three major trends in the future are massive data, social networks and mobile computing. These will bring great challenges and pressure to BI. "This requires us to innovate and integrate all the information and analyze it in real time," he said. Atul Patel said.





large data means that all datasets, including transactions and interactive datasets, are larger or more complex than the ability of common technologies to capture, manage, and process these datasets at reasonable cost and time. Tony Young, senior vice president and chief information Officer of Informatica Company, told the China Electronic news reporter that large data include large transaction data and large interactive data. For large transaction data, traditional relational data as well as unstructured and semi-structured information continue to grow in online transaction processing (OLTP) and analysis systems from ERP applications to data warehousing applications. The situation becomes more complex as businesses move more data and business processes to public and private clouds. and large interactive data, the force of this force from social media data. It includes call detail records, device and sensor information, GPS and geo-location mapping data, mass image files transmitted through the Management File Transfer Protocol, Web text and click Stream data, scientific information, e-mail, and so on.





Whether it is large interactive data or large transaction data, the processing and analysis of unstructured data is a difficult problem that the BI industry has been facing. "Both structured and unstructured data needs to be integrated." Tony Young stressed. Data integration enables organizations to combine traditional transaction data with new interactive data, allowing the business sector to form industry insights. The Exalead brand CEO Laurent Couillard also emphasizes the importance of structured and unstructured data integration access.





BI will continue to expand to BA





Traditional BI cannot handle increasingly complex data, extending BI to BA will be the focus of future competition.





as data exploded, traditional bi was unable to handle increasingly complex data. And sometimes the company's front-line staff in the implementation of high-level directives, the understanding of the senior management strategy will be biased, there is a gap between the program and implementation. Atul Patel that if there is a good communication between the executive level and the staff, the BA (Business analysis) is needed. BA is for accurate data, consistent analysis, including six pillars, namely Business Intelligence (BI), Enterprise information Management (EIM), Data Warehouse (DW), enterprise governance, risk management and compliance (GRC), Enterprise performance Management (EPM), analytical Application (AA).





"BA is different from bi, BI is more concerned with reports, analytics, dashboards, and BA is actually a bridge between ERP and BI." Atul Patel stressed.





for the six major links in Ba, bi in fact only provides an interface, you can see the dashboard and the report on BI, this is only the data input or output link. Pan, general manager of SAP China Center and Strategic Solutions, also stressed to reporters that in Ba, Eim played a very important role, such as social media or sensors produced a large number of unstructured data, EIM technology can be structured and analyzed these data. Through EIM, unstructured, meaningless data can be transformed into meaningful data.





Industry View





Informatica, senior vice president and chief Information officer Tony Young
.




data integration is the most important





Large data age has come, with the development of IT applications, enterprises accumulate more and more data. As social networks, mobile computing and sensors and other new channels and new technologies continue to emerge, the production of a large number of new data, a variety of data scattered in different systems. What are the correlations between the data? Which data is trustworthy? How to dig out valuable, easy-to-use customer information from massive amounts of data? To answer these questions, the enterprise needs a single, complete, and trusted view of the customer data. To create a single, complete, trusted view of customer data, data integration is key. There is no integrated data, its commercial value is zero.





It is important for organizations to have business units access to all data so that they can be applied to the entire large data infrastructure. Data integration enables organizations to combine traditional transaction data with new interactive data to gain insight and value that cannot be achieved in other situations. For example, through social media to understand the customer's likes and dislikes, so as to enrich customer information to improve target marketing efficiency. It is worth mentioning that data integration is not a very narrow area, its market size has reached 45 billion of dollars.





System Exalead Brand CEO Laurent Couillard





Enterprise Search improves decision quality





large data age The rapid growth of information, faster access to useful information is the key, enterprise search will become more and more important, it can override multiple management systems, databases, including the BI system, which means that BI is only one of the data sources of enterprise search.





Enterprise search platform can improve decision quality and reduce it cost. BI information is only a conclusion to decision-makers, and enterprise search can follow this conclusion, find the source and process of information, all the information through the enterprise search platform combined. Furthermore, the enterprise search platform can provide a view of full view information covering multiple systems to realize real-time running report and analysis.




When
users use bi, they tend to integrate BI products into a variety of solutions, including CRM, ERP, financial services, and healthcare applications. BI provides chambers of commerce from different sources to understand the relevant information to fully meet the needs of users, including documents, internal and external websites, case management systems and so on. However, the search for the above sources presents a huge challenge to the BI provider, which requires an enterprise search platform.




Atul Patel, vice president of Business Analysis,
SAP Asia Pacific and Japan





memory calculation speeds up analysis





in the large data age, data is stored in different states. Some data are structured, some are unstructured, some are present in media platforms such as social media, some exist in data warehouses, data marts, and it takes a lot of time to call the data. To quickly respond to changing markets, business users need to quickly get useful information and analyze it. For these challenges, we think that memory computing can solve these problems.





high-performance analysis tools that are used in memory computing support businesses to analyze business operations based on changing volumes of information. Enterprises can browse and analyze all transaction data and analysis data in real time and quickly from the data source. When a business occurs, the operational data is saved in memory, and to do an extended analysis of the entire enterprise, external data can be added to the analysis model. This analysis tool can be understood as a memory-like data Warehouse, where data is stored in a column way, which saves a lot of space. Next we want to be able to combine the trading system and analysis system to the tool, so as to avoid the layering process, which can run faster and occupy less space.

(Responsible editor: Lu Guang)