Data permeates our lives. It’s estimated that by 2025, about 463 exabytes of data will generated globally, every day.
Data is also crucial. When easily accessible, data provides valuable insights, informs business decisions, and acts as the operational bedrock for any business.
However, that isn’t always the case. Organizations with vast global footprints often face the challenge of data silos – data scattered across multiple systems with limited visibility and accessibility to members of the organization – which triggers inefficiency, provokes security risks and hinders data analysis.
Data Silos: An Operational Obstacle for a Pharmaceutical Giant
The customer is a multinational pharmaceutical company with a global presence. This leading pharma player operates 15 manufacturing facilities in India, USA, Brazil, and Mexico, and their products reach people in over 100 countries.
The customer has established themselves as one of the largest generic pharmaceutical company in the world with a key focus on anti-tuberculosis products, and they continue to drive innovation in the healthcare industry.
Consequently, the company generates an enormous amount of critical data every day that was scattered across multiple systems and applications, creating data silos that led to limited insights, inconsistent data, and reduced operational efficiency. The lack of a centralized data repository with systematic data management capabilities made it difficult to analyze and make informed decisions based on data.
To counter this issue, the customer sought a data lake solution to centralize their data collection and significantly improve data quality and visibility.
Making Data Smarter and More Accessible with Noventiq
“At Noventiq, our commitment to excellence goes beyond implementation – it's about crafting data landscapes that empower our clients to navigate vast data reservoirs with precision and clarity. Our robust data lake solutions enable businesses to dive deeper, see clearer, and thrive in the sea of information,” explained Kiran Babu - Director of Solution Sales, Noventiq India.
The implementation of a data lake involved meticulous planning and collaboration to create a strategic approach to deployment within the customer’s existing Azure infrastructure.
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Data Collection Using ETL With Apache Nifi: An Extract, Load, and Transform (ETL) process was deployed over the Azure IaaS platform using an Apache Nifi setup. This orchestrated a seamless flow of data collection from distinct sources like manufacturing plants, laboratories, etc., not only unifying data silos but also optimizing data quality.
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Data Transformation and Analysis with Apache Spark and Hadoop: Noventiq integrated cutting-edge tech to refine raw data into actionable insights. The deployment of Apache Spark and Hadoop clusters allowed the customer to transform data and streamline analysis at scale.
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Data Storage, Loading, and Visualization: Noventiq employed Azure Blob storage and a Data Mart in an MS SQL server for robust data storage and efficient data loading, and a visualization tool was deployed to enable the customer to access and analyze its data seamlessly.
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Security: To safeguard against potential vulnerabilities, the Azure IaaS components – servers, storage, and network – were dispersed strategically across the existing Azure Landing Zone, establishing a secure end-to-end flow between data collection and visualization.