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As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines
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- Automated schema change handling, data normalization and more
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Fnatic, based out of London, is the world's leading esports organization, with a winning legacy of 16 years and counting in over 28 different titles, generating over 13m USD in prize money. Fnatic has an engaged follower base of 14m across their social media platforms and hundreds of millions of people watch their teams compete in League of Legends, CS:GO, Dota 2, Rainbow Six Siege, and many more titles every year.
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FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Zendesk Sell is a sales CRM software tool that strengthen productivity, processes for sales teams and it fits your business needs with unlimited pipelines, added customization and sequences, and more. Zendesk Sell is a well moderated sales CRM to assist you expedite revenue which is quick to establish, intuitive, and easy to love. It has rich features around building lists of contacts, leads, deals, and companies.
Weaviate is an open-source, cloud-native, real-time vector search engine that allows developers to build intelligent applications with natural language processing (NLP) capabilities. It uses machine learning algorithms to understand the meaning of unstructured data and provides a semantic search engine that can retrieve relevant information from large datasets. Weaviate can be used to build chatbots, recommendation systems, and other intelligent applications that require NLP capabilities. It is designed to be scalable, flexible, and easy to use, with a RESTful API that allows developers to integrate it into their applications quickly. Weaviate is built on top of Kubernetes and can be deployed on-premises or in the cloud.
Zendesk Sell's API provides access to a wide range of data related to sales and customer relationship management. The following are the categories of data that can be accessed through the API:
1. Contacts: Information about customers and prospects, including their names, email addresses, phone numbers, and company details.
2. Deals: Details about sales opportunities, including the deal value, stage, and probability of closing.
3. Activities: Information about sales activities, such as calls, emails, and meetings, including the date, time, and notes.
4. Tasks: Details about tasks assigned to sales reps, including the due date, priority, and status.
5. Leads: Information about potential customers who have shown interest in a product or service, including their contact details and lead source.
6. Products: Details about the products or services being sold, including their names, descriptions, and prices.
7. Organizations: Information about the companies or organizations that customers and prospects belong to, including their names, addresses, and industry.
8. Users: Details about the sales reps and other users who have access to the Zendesk Sell account, including their names, email addresses, and roles.
Overall, the Zendesk Sell API provides a comprehensive set of data that can be used to analyze sales performance, track customer interactions, and improve the overall sales process.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
