Data Engineering

Stacktics thrives in the pursuit of powerful implementation of data engineering. The effective process comprises designing and building systems to enable the collection and analysis of data from multiple sources and formats. These systems follow a common pattern known as ETL, or Extract, Transform and Load. A variation of ETL is ELT where transformation takes place after data has been loaded into the warehouse. The scalability of modern databases enables data transformation being performed effectively in-database, rather than elsewhere.

Data engineers rely heavily on APIs to exchange data and the multi-tenant platform becomes increasingly relevant for conducting big data related tasks.


APIs (Application Programming Interfaces) allow the client to access and manipulate data from the server through a request and response cycle. On the web, the main protocol used to govern the request and response cycle is the Hyper-Text Transfer Protocol, better known by its acronym, HTTP


A valid request is made up of a URL, method, headers and request body. The response is constructed with a status code, headers and body. The most common formats found in modern APIs are JSON (JavaScript Object Notation) and XML (Extensible Markup Language). JSON represents data as key-value pairs while XML uses nodes as basic building blocks. HTTP headers are used to indicate the format of data that is transmitted and can be accepted by the client and server. The client can authenticate itself through authentication schemes: Basic Authentication where the credentials are included in the headers or use API keys to embed the key in URL and Open Authorization (OAuth) which allows the client and server to exchange credentials to obtain a valid access token for each request and enables authorizations with limited permissions or scopes. SOAP is an XML-based API design that has standardized structures for requests and responses. REST, which stands for Representational State Transfer, is a more open approach, providing lots of conventions, but leaving many decisions to the person designing the API. 

Multi-tenant Platform

A single-tenant cloud platform has a single software instance and its supporting infrastructure and database serve only one customer. All customer data and interactions are separate from every other customer. Customer data is not housed in the same database and there’s no sharing of data in any way. On the other hand, a multi-tenant platform is one where a single software instance and database serves multiple customers. While the customers can only see their own data, the rest of the data lives in the same database and the same computer engine processes all the data. Multi-tenancy is at the heart of effective SaaS operations because it makes it easy to build and deploy applications faster and to scale those applications quickly. A multi-tenancy platform also provides efficient resource usage at a reduced cost due to shared users.

Connect with Stacktics and let your organization transition to the powerful realm of effective data engineering.

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