Information is the oil of the 21st century, and analytics is the combustion engine
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Ever since the dawn of web 2.0 and migration of Desktop based applications to web based cloud applications, the exponential rise of data that’s generated in the last decade has been unprecedented in the history of software technologies.

The sheer size of the data has made the businesses face with challenges when it comes to making sense of this massive data and exploring best practices to manage the integrity of data in a meaningful way. This has led to a complete new industry in the data management domain that uncovers the secrets hidden in this vast ocean of data that can give businesses key insights into developing future strategies and competitive advantage. This is what Big Data is and We at WebPropellent has been at the forefront of establishing big data practices across wide range of industries helping businesses manage quintillions of bytes of data every day.


Big Data Strategy Framework

We help businesses find the right approach to collecting and connecting with data, irrespective of the volume of data that is generated across the business cutting across continents and various data centers. Our Strategy Framework is a set of best practices we have formed based on years of experience that pinpoints the bottlenecks in the speed of data generation, resilience, storage, redundancy and analysis. We help organizations connect the dots across various data silos helping them generate actionable insights.


Big Data Infrastructure Set-Up and Support

Whether your business is a large multi-billion dollar biotech research firm generates billions of data points from DNA information or massive online streaming services company with millions of concurrent users at any given time of the day, the speed at which information is generated is massive and needs the right set of technologies to ensure data is scalable, manageable and secured at all times. At the same time, extracting knowledgeable intelligence for making dynamic business decisions requires the right combination of software technologies with hardware and a deep expertise in implementing it a tailored way to address the needs of your business. This is where we provide a great deal of ease to our clients because we help them establish the right hardware on-premises or over the cloud or a hybrid structure with outstanding levels of technical support unparalleled in the industry.


Big Data Development

We help you with Data Archiving, ETL offloading, Governance and Security Management, Self-Service Business Intelligence, Streaming Analytics and Data Lakes Management at scale thereby ensuring all your data warehousing needs making you get the right information and at the right time ensuring business continuity, competitive edge and 360 degree data lifecycle management. We help you with custom big data application development, big data integration services, line of business integration and enterprise application integration services and data migration services.


Big Data Analytics Services

The grand goal of any business deploying big data technologies is to harness the analytical capabilities of such technologies and gain insights into their businesses for better decision making and explore new actionable steps. We provide our clients with



Big data is characterized by its immense volume. It includes terabytes, petabytes, or even exabytes of data, often far beyond the capacity of conventional databases. This data can come from a variety of sources, such as social media, sensors, devices, and more.



Big data is generated and collected at an incredible pace. For example, social media posts, sensor data, and e-commerce transactions occur in real-time or near-real-time. Managing and processing this continuous stream of data is a key challenge in big data applications.



Big data is heterogeneous and comes in various formats, including structured, semi-structured, and unstructured data. This diversity includes text, images, videos, log files, and more. Managing and making sense of this wide variety of data types is a fundamental aspect of big data analytics.



The ultimate goal of working with big data is to extract value from it. This value can come in the form of insights, patterns, or predictions that can inform decision-making, improve business processes, enhance customer experiences, and more. Big data analytics, machine learning, and data mining techniques are used to derive this value.

Visualization & Analytics

Kibana, Tableau, D3, Qlik, AWS Quicksight, IBM Cognos


Hadoop, Kafka, Spark, Storm, Hive, Fink,

Distributed Warehousing

AWS EMR, Cloudera, Teradata, Spark, Greenplum


Hbase, MongoDB, Elasticsearch, Couchbase, Cassandra, MariaDB, SAP Hana



Big data and LLMs handle large datasets effectively



They derive meaningful insights from vast amounts of information.



Automates data processing and decision-making tasks.



Enhances user experiences with tailored content and services.

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