Data is vital in today’s day and age. Companies are dealing with huge amounts of data scattered across different locations and different sources. It is available in different formats, structured or unstructured. So to manage this vast complex data, we have a one-stop solution called the ETL tool.Â
ETL tools are programs that integrate all three processes into a single application. Talend ETL is one such tool.  Â
ETL stands for Extract, Transform, Load.Â
Extract: It is the process of reading the data from heterogeneous or homogeneous sources.
Transform: It is the process of cleaning the data, analyzing, and applying various functions to convert it into meaningful results.
Load: It is the process of transferring the processed data to the target location using minimal resources.
There is a race going on today in big data. In this intensely competitive world, Talend is a leading unified platform for data integration that enables every company to harness the power of their enterprise information to get ahead. Talend is like a critical infrastructure for a data-driven world. It’s built for the modern big data and cloud-centric environment, allowing businesses to turn data into actionable business insights.
Talend is an open-source software integration platform or a vendor that offers data planning, data quality, data integration, application integration, data processing, cloud storage, and big data software solutions. It helps businesses becoming data-driven by making data more accessible, enhancing the data quality, and quickly moving the data to where it is required for real-time decision making.Â
Talend first joined the market in 2005, becoming a leader in the area of commercial open source data integration applications. Founded on the simple premise that there has to be an easy way for people to connect with their data. Using the power of the open-source business model, Talend is set out to modernize the data integration market. The company is led by some of the brightest minds in Silicon Valley. They share a mission of helping companies operate with real-time insights about their customers, markets, and business and translate them into a competitive advantage.Â
Talend Product Suites has three broad categories:
Talend Platforms: This includes platforms like big data, data management, data services, hybrid clouds, and enterprise integration.
Talend Enterprise: This is the licensed version that includes cloud integration, data integration, data preparation, and big data.
Talend Open Studio: TOS for data integration is a widely used Talend ETL tool. TOS can quickly merge, transform, and upgrade data from a variety of sources. TOS umbrella includes MDM, ESB, BPM, data quality, data integration, and big data.Â
Industry: Media and Entertainment
About
Orange: Since 2006, Orange has been the leading group brand in internet, television, and mobile services in most of the markets. It also provides telecommunications services to businesses worldwide under the Orange Business service brand.Â
Use Case: Sales CommissionÂ
Challenges: Improving revenue commission with vendor partners by analyzing the sales data. Results:Â
The challenges of integrating and systems were hard two decades ago when all systems were on-premise. Now, this is even more complex and important since most of the companies have systems in the cloud such as salesforce, CRM, or Marketo. They are moving more and more of their data and applications to cloud platforms like Amazon web services. Now they need to connect their systems from the cloud to their own premise data sources and vice-versa. Â
Talend data fabric is a solution with the capability to meet companies’ data integration needs regardless of whether the data resides in the cloud or on-premises, running in real-time or batch. It connects all enterprise systems to empower companies to drive their business in innovative ways never before possible.
If you are interested in making a career in the Data Science domain, our 11-month in-person Postgraduate Certificate Diploma in Data Science course can help you immensely in becoming a successful Data Science professional.Â
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