Data Integration for Cloud Data Lakes: Architecture and Best Practices - White Paper
Having the ability to make accurate data-driven business decisions in near real-time is a practical necessity in today’s fast-moving business environments. However, data silos often hinder an organization’s ability to be nimble with their data. The process, time, and effort it takes some organizations to aggregate data from dissimilar sources can often cause them to miss out on opportunities. In the meantime, it’s difficult to cultivate confidence in data across an organization without an easy and transparent method to manage data integrity and impose data governance.
A cloud-based data lake storage system offers a central reservoir that everyone is able to access. This allows companies a single location from which to harvest and leverage data in business opportunities and open potential new business prospects. This architecture is revolutionizing the way organizations access data in today’s ever-changing world.
An example of this is a custom data lake we built for a client that helps support targeted TV advertising. Their data lake essentially gathers customer viewership and advertising campaign data, as well as customer targeting details that are then used to help evaluate a campaign’s overall performance and reach. It also assists the client to gauge consumer behaviors, predict outcomes, and establish whether current ad campaigns are operating as anticipated.
Having the capacity to harness and work with data from different sources begins with owning a central repository where data from dissimilar origins gets ingested, processed, explored, and put into use. In this white paper we will review the data lake architecture and best methods we use for this and other projects to attain effective business outcomes.
To read more, download the white paper by clicking on the image below:
PDG has expertise in cloud based data lake technology and storage, and business intelligence technologies—including Apache Spark, Hadoop, Kafka, Amazon Glue, EMR, Kinesis, Firehose, Athena, Microsoft SQL Server Integration Services and Analysis Services, Hive, Presto, NoSQL databases, and Elasticsearch.
Contact us to learn how we can help you implement a custom tech stack based on your data strategy and business objectives to help you reach your ROI goals.
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