How to build a scalable data architecture and industry best practices

When building a data analytics stack for your business, it is very important to choose the right tools, technologies and frameworks to future proof your stack. Based on your data size and analaytics needs, it is important to choose the tools which support your requirements well. Unfortunately, organizations often make the mistake of not choosing the right tools and technology which leads to dashboards not loading timely and increased downtime of data apps.

• Why is having a scalable data architecture important for your organization?
• How to build a scalable data architecture? What measures to take?
• What tools and technologies to consider?
• Industry best practices

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Ali Mojiz – CEO/Head of Analytics and Data Science | Data Pilot

I’m a full-stack data scientist with extensive experience in helping organizations become data-driven. I’ve been in the data space for the last seven years. I started my career with an ETL/BI Consultancy firm (2015) as an ETL/BI Engineer. I implemented end-to-end BI and DWH solutions for banks and insurance companies using tools like Talend, IBM Datastage, IBM Cognos, OBIEE, SQL etc. After that, I switched to Modemetric where I I worked as a data analyst in their predictive analytics department. That’s where I helped the company build a predictive analytics module as part of their BI product called Lantern. Side by side, I did a lot of online courses and started my Master’s in Data Science at the University of Illinois. After building the predictive analytics module, I switched to NETSOL Technologies as Lead Data Scientist, leading the AI/ML team at NETSOL and OTOZ Mobility. That’s where I used tools like Tableau, Metabase Power BI, Python, R, Azure ML, Azure Databricks etc. I architected the complete data architecture of OTOZ, which is being used by Drivemate, one of the biggest car-sharing platforms in Thailand. I also built many ML models for the captive finance market with clients like Nissan Finance, Hyundai, CNH etc. In Jan’21, I started Data Pilot (Pilot (w.data-pilot.com), an analytics and AI/ML services company. We wing with clients in the United States, the United Kingdom, Saudi Arabia, Australia, and Pakistan.