Etl Data Integration

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Talend Open Studio v4.2.0m2 releases ETL open source software vendor

Talend (stepping Blue) is the first http://www.aliyun.com/zixun/aggregation/13607.html "> Data Integration Tool Market ETL (data extraction extract, transmission transform, Load load) Open source software vendor. Talend provides an entirely new vision for ETL services with its technical and business dual model. It breaks the traditional exclusive closed service and provides a public ... for all sizes of companies.

Translating large data into large value practical strategies

Today, some of the most successful companies gain a strong business advantage by capturing, analyzing, and leveraging a large variety of "big data" that is fast moving. This article describes three usage models that can help you implement a flexible, efficient, large data infrastructure to gain a competitive advantage in your business. This article also describes Intel's many innovations in chips, systems, and software to help you deploy these and other large data solutions with optimal performance, cost, and energy efficiency. Big Data opportunities People often compare big data to tsunamis. Currently, the global 5 billion mobile phone users and nearly 1 billion of Facebo ...

Mining business value from large data

Both in the public and private sectors, organizations and businesses are collecting and analyzing "big data" to more accurately forecast market trends and make smarter decisions to ensure success. They classify large amounts of data from a variety of sources, including weather forecasts, economic reports, forums, news sites, social networks, wikis, tweets and blogs, and then analyze the data further to understand their customers, operations, and competitors from a new perspective. Some companies even use predictive analysis to determine what they might encounter in the next one months, year or even five years.

What is the difference between database integration and large data technology?

As two of the most popular technologies in the field of information management, the hardware architecture of database integration machine and large data technology is basically the same, but the software system has the essential difference, which leads to the different characteristic performance. With the rapid growth of enterprise data and the continuous improvement of users ' requirements for service level, the traditional relational database technology has shown obvious lack of ability in production practice for a long time. How to obtain high availability of massive data at reasonable cost has become a major challenge in modern it field. In order to meet this challenge, in recent years, it market ...

Cloud practice and large data outlook

Zhang Fubo: The following part of the forum is mainly four guests, talk about cloud practice. Beijing First Letter Group is the Beijing government's integration company, mainly responsible for the capital window of the construction, they are also in the domestic, in the government industry earlier in a company, as the first letter Group Technical Support Center General Manager Zhang Ninglai for us to do the report. Zhang: Good afternoon, we have just introduced, I am from Beijing First Letter Development Co., Ltd., I bring today is the result of our practice in cloud computing technology these years. Today is mainly divided into three parts, we mainly do is the field of e-government applications, we are mainly ...

Talend the Open Studio for data integration 5.1.0rc1 publish the database integration and synchronization tools

Talend open Studio for data integration is an open source data extraction, conversion and loading tool (ETL). It can perform synchronization from http://www.aliyun.com/zixun/aggregation/8302.html "> Data Warehouse to Database, as well as file format conversion, with a graphical interface based on Eclipse RCP, Generate a Perl or Java related number script. The 8639 ....

Large data age: integrating large data and data warehouses

Integration strategy Data integration refers to the combination of data from different systems for business users to study different industry behavior and customer behavior data processing methods. In the early days of data integration, data was limited to trading systems and their applications.   The development of business decision is guided by the decision platform, and the limited dataset provides the foundation of creating the decision platform. Data capacity and data types have grown dramatically over the past 30 years, with data warehousing technology from scratch, and infrastructure and technology to meet analysis and data storage requirements. All this has revolutionized the prospects for data integration. ...

Website Data analysis: The premise of analysis-Data quality 3

The intermediary transaction SEO diagnoses Taobao guest Cloud host technology two articles in front of the hall--analysis premise-Data quality 1 and premise of analysis-data quality 2 The statistic information of data profiling is introduced, and the data auditing is used to evaluate whether it is stored In quality issues, the quality of the data can be reviewed through three aspects of completeness, accuracy and consistency. This article introduces the last piece-data correction

The confusion of big data

It has been almost 2 years since the big data was exposed and the customers outside the Internet were talking about big data. It's time to sort out some of the feelings and share some of the puzzles that I've seen in the domestic big data application. Clouds and large data should be the hottest two topics in the IT fry in recent years. In my opinion, the difference between the two is that the cloud is to make a new bottle, to fill the old wine, the big data is to find the right bottle, brew new wine. The cloud is, in the final analysis, a fundamental architectural revolution. The original use of the physical server, in the cloud into a variety of virtual servers in the form of delivery, thus computing, storage, network resources ...

Large data age: integrating large data and data warehouses

Integration strategy Data integration refers to the combination of data from different systems for business users to study different industry behavior and customer behavior data processing methods. In the early days of data integration, data was limited to trading systems and their applications.   The development of business decision is guided by the decision platform, and the limited dataset provides the foundation of creating the decision platform. Data capacity and data types have grown dramatically over the past 30 years, with data warehousing technology from scratch, and infrastructure and technology to meet analysis and data storage requirements. All this has revolutionized the prospects for data integration. ...

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