Home / Focus Areas

Purpose Built Solutions

Data Engineering

Data is omnipresent. Constantly evolving and churning, it is the life force of any business. The ability to harness it and unlock its full potential determines the trajectory of a business. We partner with our clients to solve complex problems of big data infrastructure and data engineering; with scalable analytics and data platforms that power digital experiences and provide actionable insights, we bolster data-centric business models. 

Client Stories

Post Image

To ETL or Not to ELT: Choosing the Right Approach for Data Processing and Management

Deciding between Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) is one of the most important decisions a data engineer has to make. Transforming data before loading (ETL) or after loading (ELT):can shape how efficiently we handle datahow flexible we are in adapting to changing requirementsand how well we scaleAs a data engineer, I've had many opportunities to work with various data pipelines and tools. A commonly asked question is 'Should we use ETL or ELT?'. Both methods have...

Read

Data Drives Innovation and Growth at Australian Fintech

A tailored strategy combining software engineering, data engineering, and ML operations enabled data-led business decisioning for a fintech enterprise. Our client, a leading Australian non-banking fintech providing digital instalments and lending services to customers across Australia, New Zealand, and Singapore, was facing a unique challenge. Having acquired and integrated several small businesses over the years, the company was grappling with a mix of disparate and legacy systems and processes, making it extremely arduous to build critical components around Machine Learning...

Read

Driving Data-led Decision-making through Data Engineering for Superior Business Impact

Springer Nature is a global academic publishing company that advances discovery by publishing trusted research. Following the 2015 merger and subsequent growth with the acquisition of products, the company’s workflows became inundated with multiple systems and different data models driving article submissions from authors - a key business process.  Data analysts across different teams would use several manual processes while navigating a complex ecosystem of multiple data stores to build an aggregate view of the business, identify trends and support...

Read

Blogs

Post Image
Choosing the right tool while building your Data Platform: DBT vs. Spark(By example)

Written by: Niranjan Ingale Table of contents What is a Data Platform, Spark & DBT: Let’s start with some definitions Data Platform: A data platform is a comprehensive infrastructure that facilitates the ingestion, storage, processing, analysis, and management of data...

Data Engineering

Sahaj Software

Post Image
Citizens of The Great Barrier Reef — A story of scale, complexity and collaboration for conservation

The Great Barrier Reef, Australia’s iconic ecological site, is not only important to the continent but to the planet as a whole. With over 3000 individual reefs stretching over 2000 kms and home...

Data Engineering Sahaj Impact

Anand Iyengar

Passwordless Auth between Cloud provider and Github

I discuss how I deployed my app to AWS Amplify through Github actions. However, you can deploy to any cloud provider and service of your choice by following this method.

Data Engineering

Anirudh Ramesh

Our Clients