How to become a data-driven high-velocity enterprise

It’s an exciting time to be a Data Engineering and AI / ML professional. Data has come a long way from being a back-office function used for reporting to being central to every business. FANG (Facebook, Amazon, Netflix, and Google) created multi-trillion-dollar enterprises by collecting, storing, analyzing, connecting data and then bringing insights, predicting behaviors, prescribing solutions using artificial intelligence and machine learning. From there, every enterprise, big and small, digital native or traditional, has realized that they need to have data in the front and center of their business.

Businesses like manufacturing and logistics capture data from every endpoint of the shop floor, supply chain, and top floor to optimize cost, reduce time to market, and create innovative products.

Retail, consumer services, travel, and hospitality businesses are getting to know their customers in the best possible way, making it a “segment of one.” They capture user interaction in each user contact interface to reduce friction, improve processes, and suggest the best product and services the customer needs and wants.

Banking, financial services are leveraging data and AI / ML to make better lending decisions, reduce fraud, improve trading algorithms, fight financial crimes, and help customers reach their full financial potential. Data and analytics are making a life-changing impact in healthcare and the life science industry to help discover lifesaving drugs, improve diagnosis, and improve healthcare reach by data democratization.

All this is becoming possible as we see rapid strides made by the tech industry to create game-changing platforms and products. For decades industry worked with traditional data warehousing and reporting techniques with RDBMS (expand) and ETL tools aided by OLAP reporting.

With the advent of Big Data, we can rapidly store structured and unstructured data and compute-intensive analytics on terabytes of data. But concurrency and consumption challenges remained, and the industry struggled to break data silos.

With the rapid adoption of the cloud, this scenario is changing. Snowflake revolutionized data computing by separating storage and computing. Databricks democratized machine learning to enable citizen data scientists to deploy machine learning at scale. AWS, Microsoft Azure, and GCP today are offering new groundbreaking capabilities almost every day. And then, there are many niche products offering solutions for Natural Language Processing, Text mining, voice analytics, computer vision, etc.

That’s where you need a partner you can trust, who can help you navigate these complexities and deliver the business outcomes to be ahead in the market. Zensar is ready to bring velocity to your business initiative. At Zensar, we provide an integrated “Experience to Engineering to Launch” approach that combines strategy, design, and implementation. You can now ideate and launch MVPs and then scale them faster than the competition.

We have recently organized Zensar under five services to scale digital initiatives. Data Engineering and Analytics is one of these five towers.

Our mission is to create communities of experts in data engineering on the cloud, analytics, automation and drive AI-led innovation. We have brought together the rich experience of Zensar teams over the last 20+ years to build reusable platforms, solutions, and frameworks to bring velocity to deliver the business transformation for our customers.

Our strategy will bring synergy across four pillars of our strength to deliver velocity for our customers.

• Drive speed by leveraging Zensar’s platforms/solutions for Data and Analytics.

• Pair this with the community of in-house experts who continuously go through upskilling and have expertise in the latest technology stack in the industry. This team is complemented by market hires and emerging talent to provide scale.

• M3BI (acquired by Zensar in July 2021) is a niche data engineering and analytics firm with deep experience in big data, analytics, and AI / ML. M3BI has successfully executed large and complex transformation programs for Top 10 players in BFSI and Healthcare

• Effective partner ecosystem (hyper scalers, leading cloud data warehouse products, niche visualization and AI / ML products) to provide the best in class solution. At the same time, being an independent service provider, we can provide product-neutral objectivity to customers.

Data Engineering and Analytics service line covers the complete value chain (of Data Governance, MDM / CDP, DQ, Cloud Data Engineering, BI, Visualization, Analytics, AI, Machine Learning, Intelligent process and IT automation) to drive business value.

Reach out to us if you want to know more about the interesting engagements we are delivering on field.

1. From on-premise to hybrid/cloud-based data platforms.
2. From batch to real-time data processing.
3. From rigid data models to flexible, extensible data schemas.
4. From time-intensive to accelerated analytics and data science.
5. From point-to-point to decoupled data access.
6. From manual to automated data-to-insights lifecycle.