What We Do
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As the amount of data has been continuously increasing from IoT devices, social networks, data streaming devices, emails, mobile apps, databases, and many other sources, most organizations are looking to move from traditional data warehouses to data lakes. VVDN has a deep experience and capability in implementing end-to-end enterprise data lake solutions by focusing on identifying the data, connecting with a variety of data sources, and transforming the semi-structured and unstructured in real-time or batches that can hold a vast amount of raw data in native format until required for data analytics and business intelligence.
At VVDN, we help customers getting meaningful insight in digital transformation journey by helping them design and deploy custom data lake solution that offers the client with
VVDN help organizations leverage the full potential of data lake solutions for different domains and multiple applications as required:
Brings disparate data together from network devices to optimize network performance, network analysis as per location and time, health monitoring of network devices, management and performance to mitigate risk, improve customer targeting, and many others.
Enables ingesting several Terabytes of data per day from the network, business, and other sources to help measure mobile network QoS, develop new products, improve customer experience, reduce churn, optimize network value, monitor network infrastructure, and other different applications.
VVDN cloud & apps team have deep expertise and experience in the latest data management, optimization, and analytics tools such as HDFS, Cassandra, Apache Spark, AWS lake formation, Kinesis, Elastic search, Azure Blob storage, Synapse analytics, and many others
Our team has helped organizations with streamlining the complete solution by deriving high-value intelligence from real-time business insights
Define different layers of data lake including data source, data management, and optimization, ETL state to optimize as per the client’s existing needs and meet business objectives.
Complete architecture implementation from varied data ingestion i.e structured, unstructured, and semi-structured data to data storage, data preparation, data governance to data discovery, and security.
Our team of experts helps perform data analysis on the transformed data by using different analytics algorithms and tools for Interactive analytics, big data processing, machine learning, real-time analytics, and operational analytics.
Our experts focus on optimizing the storage setup by focussing on data virtualization and data masking.
We focus on automating testing for ingestion, storage, data processing, data distribution, data lineage, metadata, data visualization, data mining, and ETL automation using different scripting languages.
Enables migration from the on-prem data lake to the public cloud or from one public cloud to another as per specific business requirements.
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