Relus Cloud & Big Data on AWS
Organizations create a variety of data at different volumes and velocities. The data can reach unprecedented levels, making it challenging to decipher relevant information. Relus can help you tackle the challenges associated with huge data sets, structured and unstructured data and real-time responses.
Relus Cloud’s Big Data Practice provides the expertise, tools and insight you need to create customer-centric, data-driven strategies that can transform your business and create new avenues for growth. Leveraging the Amazon Web Services product suite, Relus Cloud gives businesses a fast way to build highly scalable, cost-effective and secure Big Data solutions. We can build turnkey solutions or help you get your existing team up to speed in a matter of weeks.
Relus Big Data Practice
PLANNING YOUR DATA VISION
FAST PROOF OF CONCEPT
Big Data Use-Cases
DATA WAREHOUSING & ANALYSIS
IoT & DEVICES
EASY MAP/REDUCE CAPABILITIES
AUTOMATE CODE DEPLOYMENT
Featured Big Data Resources
Thanks to the Amazon Lex bot creation console, applications can now leverage this level of deep-learning. You can build a device, design its conversations, and test it as an end user would experience it.
The marriage between technology and education began with simple games and tutorials, however it quickly transformed educational needs with new platforms, software, and portals. Now surrounded by technology, education professionals require simpler options for managing technology in their environment.
31 Flavors of Data Science In today’s environment, nearly every organization is using data analytics to adopt a more data-driven approach to understand their customers, whether to inform their marketing strategy or otherwise. When I speak with our Big Data team about...
Artificial Intelligence (AI) is the hottest technology disruption of 2017. Integrated components of machines will soon enable a small mechanism to run a full analysis and decision process on coin-sized hardware. Until this effort becomes reality, however, the complicated analytical tasks of AI will continue to require a great deal of compute power.
Tremendous value can be found in an organization’s data lake. This is especially true with the decreasing cost of storage during the last few years.
You no longer need a cluster of servers, or a single EC2 instance, in order to perform ad-hoc queries on your data. Instead, Athena charges only for the data that is scanned during the query process, even forgiving charges for items such as DDL statements and failed queries.