Data Engineering and Architecture Development

You might have different data sources with different formats, and you need to consolidate these data sources and putting them in central repository.

Selecting and building the right data infrastructure and architecture you need is complex. From ingestion, storage, processing, and access, you need to consider ingestion technique (batch or real time), scalability, tools, platforms (on premise, on cloud, or hybrid), frameworks (open source, proprietary), integration, adoption, migration, and security.

Based on your need, we help you to build the right data infrastructure solution for your business:


  • On-Premises architecture development Solution: On-premises solution enables data to be stored locally at the organization. This option has its own advantages and disadvantages. If the organization is more interested in greater flexibility and security, on-premise is the solution. We can help you developing the architecture of on-premises infrastructure using free and powerful open sources tools.


  • On-cloud infrastructure Solution: Another solution is building data infrastructure on the cloud. This works by transmitting and storing data at the sites of vendors such as Amazon Web Services (AWS), Google Cloud or Microsoft Azure. We can help in consulting which cloud platform best suits for your business.


  • Hybrid Solution: You might have interest having both on-premise and cloud infrastructure. In this regard, we can help in building the hybrid infrastructure for better accessing and processing data.


  • Data pipeline development Solution: Data is meaningless if you can’t access it to gain insight. Once your data is stored in central repository, the next step is processing and analysing the data. Since Data Science is a process, we can help you by developing a data pipeline that can help you from accessing the raw data, data wrangling to machine learning model development and deployment.