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. UniSpark 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 UniSpark, 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
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.