At Polestar, we provide organizations with cutting-edge data management services and data engineering solutions by taking into account their existing business, data and technology stack such as their data architecture, digital maturity and hosting environment.
Our robust QA and QC practices help to seamlessly integrate cutting-edge data engineering technology into their existing or legacy systems, and our 24x7 on-site and remote support help organizations extract maximum ROI.
Our data warehouse services help decision-makers extract information from diverse data sources: RDBMS, Data Marts, APIs, etc. Our solutions help bring all this data into a single place, enabling organizations to build transformative solutions
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Today, cloud computing has become an essential strategy for businesses that want to capitalize on the scalability, agility and cost-effectiveness of cloud computing. We provide cloud data management services on leading platforms, such as Azure, AWS, Google Cloud Platform.
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With our Big Data management services, we implement Big Data analytics applications that are highly scalable and high-performance within an agile framework. Our solutions provide high ROI to the enterprises, with reduced risk, implementation time and cost to our clients.
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We design and develop enterprise data lakes to give organizations the capability of performing advanced analytics on data of any size and ingest real-time data at scale. Our offering delivers data lake strategy & roadmap, data integration, access & services, data lake implementation & go-live enablement.
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Leading businesses stay relevant through incremental improvement in their processes. This century-old Consumer Electronics company had a knack for evolving with the market.
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Leading businesses stay relevant through incremental improvement in their processes. This century-old Consumer Electronics company had a knack for evolving with the market.
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Leading businesses stay relevant through incremental improvement in their processes. This century-old Consumer Electronics company had a knack for evolving with the market.
READ MOREEDM comprises many sub-processes, such as data collection, data ingestion, data preparation, data storage, data visualization, and data analytics.
Whether on-premise or hybrid, a cloud framework is the most ideal for Enterprise Data Management because it offers a highly agile, scalable, and cost-efficient framework for seamless data storage and access.
Formulating enterprise-level Data Governance policies for data storage, collection, and analysis is vital to building an EDM framework. It is the crucial step towards building a single source of truth towards achieving true Data Democracy.
