Run and Scale Analytics in Seconds With AWS Redshift
13. 06. 2022
Whether you are beginning your analytics journey, looking to extend your existing capabilities for broader reporting and insights or have a pre-existing solution but are realizing your need for greater flexibility or scale, Redshift offers your enterprise a high caliber platform.
From Adastra's 20+ year history, we have extensive experience in implementing and modernizing legacy systems. We will leverage best practices and accelerators to implement Redshift, ensuring that you achieve fast-tracked delivery and value from your analytics engine.
The success of modern businesses relies on the prioritization of data-driven decision-making through results-oriented analytics. At their core is a modern, scalable, and cloud-based platform tailored to deliver fast value-add insights. Whether you are beginning your analytics journey, looking to extend your existing capabilities for broader reporting and insights or have a pre-existing solution but are realizing your need for greater flexibility or scale, Redshift offers your enterprise a high caliber platform.
As part of a modern architecture, organizations inevitably implement a Data Lake to support their analytical needs, but this is just the beginning of the journey. Typical organizations will need a robust database to allow the democratization of analyses to a large number of users across the enterprise, handling various use cases and complexity. Amazon Redshift, working in tandem with Redshift Spectrum and Amazon S3 enable a Lake House Architecture, combining the best of the Data Warehouse and Data Lake platforms.
Early adopters of Data Warehouse have implemented solutions like Teradata, Oracle and Netezza, which could handle large volumes of data but at a high price point. Later implementations of SQL Server had a lower price point but all of them were limited in their ability to support analytics in a true Big Data world, thus imposing constraints. Redshift has a lower price point than all those options, by orders of magnitude at times. More importantly, it does not suffer from the same limitations and will not constrain an organization from any use cases it is considering.
Despite the costs associated with early Data Warehouses, some organizations made good use of them and still had an upper hand amongst their competitors. Over time, standards and architecture evolve drastically increasing the costs required to maintain the older platform. The business needs to evolve even more drastically and often to a point when the EDW fails to keep up.
An EDW can be improved but at times, it is simply more strategic to rebuild and rearchitect the solution, as both technology, business needs, and priorities have changed too much. A migration to the cloud, combined with a modern architecture including Amazon S3 and Amazon Redshift should be part of the new data landscape.
Allows for scale and flexibility in the scope of your data warehouse. Costs start with as little as 25c per minute.
Scales to hold petabytes of data and enables querying of exabytes from your data lake. Allows advanced optimization to further optimize performance up to 10x.
Ability to analyze structured or semi-structured data in Amazon S3 with Redshift Spectrum
Automated backups, patching, recovery, computing infrastructure, load balancing, planning, scheduling and execution of S3 queries
Industry-leading security and encryption techniques to keep your data safe both at rest and in transit. The platform is certified to meet all common regulations.
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