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1、数据管理驱动 企业数字化转型Presenter2019-08-14 14:02:47-We at Informatica recognize that data is the trusted currency of business and so do our customers.Theyre telling us its a board room level conversation at this point, and the future of their businesses depend on how effectively they can leverage their data
2、assets.- Siemens quote https:/www.weforum.org/agenda/2018/01/3-things-change-medicine-2018-big-data-healthcare/ - Novartis quote Forbes contributor quote (not a company)数据就如同飞机的燃料Presenter2019-08-14 14:02:47-But its not easy to manage in the world of Data 3.0. Data 3.0 Summary script: Over the years
3、, youve had to change the way you think about and manage data. And weve evolved along with you. In Data 1.0 (circa 1960-2000), data was used in specific business applications, like payroll automation, airline reservations or retail transactions. Informatica helped you thrive in that era by defining
4、the ETL (Extract Transform Load) market and leading in Data Integration.In Data 2.0 (the last 15-20 years), data was used to support enterprise-wide business processes, like supply chain, straight-through processing, and quote to cash. Informatica helped you thrive in that era by expanding our capab
5、ilities to add data quality, MDM, cloud data integration, data security, data archiving, and other data services.Data 3.0 (which we have now entered) is the next generation of data where data enables entire businesses to be transformed through new business models and processes. Back to slide statsTh
6、ere are five key technology shifts that are all converging at the same time. Any one of these would be a significant trend by itself. All five of them coming together is what makes this a generational market disruption. First of all, data volume continues to grow - data doubles every 12 to 18 months
7、 for most companies. That has not stopped. That has been the case for the last five years and as far as we can tell that is going to continue. Second, the types of users and the number of users accessing that data. It used to be that an application was in control of the data. Then you had analytical
8、 platforms, BI tools, reporting tools, visualization tools, creating tools, etc. that wanted access to the data. And now in addition to all of that, you have these knowledge workers, the new users estimated at over 500 million people right now - who directly want access to the data. Youll hear about
9、 it as data self-service or democratization of data and so on, and that is another growing trend in the use of data. A pivotal trend are the new types of data - unstructured data, mobile data, social data, IoT data. That is a huge trend that is only increasing. Also data in the cloud. Over 90% of al
10、l data is expected to be in the cloud by the year 2020, which means that between now and then, data in the cloud will grow by about 10x compared to overall data doubling every 12 to 18 months. So, the growth of data in the cloud is going way faster than the overall data trend. The last big trend is
11、machine learning and AI, both as a consumer of data as well as a supporter of data management processes. As a consumer, AI leverages new types of algorithms that customers are building that all require vast amounts of data.But the use of machine learning and AI also makes data management more effect
12、ive which is something that we do using our platform. So, if you look at these five trends - and theyre all happening simultaneously - thats what makes it a generational market disruption. STATS New stats from Gartner 100 Data and Analytic Predictions fro 2021 research ( By 2020, 80% of organization
13、s will initiate competency development to improve data literacy (Gartner)By 2020, its estimated 40% of all analytical projects will cover at least one aspect of customer experienceMDM/EDC feeds AI: “The output of both AI and ML is only as good as the input; initial data quality must be high. Therefo
14、re, companies will need a means of collating, combining, and translating large stores of data into a 360-degree view of individuals; such as a centralized hub.” (Gartner) By 2020, digitally trustworthy companies will be 20% more profitable. (Gartner)By 2020, more than 40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists. By 2020, 25% of large organizations will be either sellers or buyers of data via formal online data marketplaces. By 2020, large global-enterprise use of data masking o
