Cloud Data Platform – RM Dayton Analytics

Some see cloud as technology. We see it as an opportunity to revolutionize business processes and innovate throughout industries. New high-octane technologies provide access to nearly unlimited resources anytime, anywhere, and in any amount.

You see cloud as an integrated approach leveraging the proven cloud providers such as AWS, Azure, and Google Cloud to bring you world-class solutions. We can provide the right talent to accelerate deployment and deliver the scalability and agility capabilities needed to help capture the transformative value of the cloud.

Cloud puts insight at the heart of your business and agility into the hands of your team, the dynamics to delight your customers. We can provide skill technology and functional leaders to help accelerate operations across single, multi, or hybrid cloud environments. Leveraging hyper-scale cloud solutions that deliver rapid deployment capabilities, you can harness the power of cloud and realize better business outcomes.

New ways of connecting with customers, disrupting markets, and creating business value. A move to cloud can make faster innovation and more flexible operations possible. But if it doesn’t ultimately help find new ways of connecting with customers, creating business value and simplifying management of key business applications, you would not be wrangling the full benefit of cloud.

By coupling hyper-scale cloud technologies with our talent supply chain, we can help you build and execute a pragmatic cloud strategy that can help make your cloud vision a reality.

rmda-ss-blockchain-network-global-decentralized-database-galatic-nebula-future-world-3d.5689.3500

Enterprise artificial intelligence vs. intelligent automation: what’s the difference?

February 28, 2023

Revolutionizing how money moves: leveraging AI and cognitive technologies

February 2, 2023

Bridging the acceptance gap: how we will learn to trust enterprise AI?

Cloud Services

The Cloud enables us to innovate business systems and processes, providing unparalleled access to vast resources, wherever and whenever we want them. It starts with an understanding of the tech to realize the disruptive nature of cloud solutions.

Cloud Stategy

We align cloud knowledge workers to business goals, gaining an understanding of your business, identifying and solving key challenges while not letting cloud for technology’s sake obscure our objectives.

Cloud Infrastructure

Cloud Infrastructure Services help companies achieve desired business outcomes by combining knowledge worker business acumen with an array of technical services. Managing your overall infrastructure can take up a great deal of attention, putting a strain on both the sourcing efforts of your HR folks, as well as your IT resources. By streamlining your alignment processes, you can focus on business innovation.

Cloud Migration

Migrating workloads to the cloud can help reduce your physical IT infrastructure footprint and associated costs. Filled with risk, migrations without the right key resources can sink the best of intentions. In addition to the technological aspect, migrations should consider factors such as team capabilities and dynamics.

Re-engineering, performance and optimization

Implement the right architecture for multi-cloud, hybrid, or cloud-native applications

Re-engineering

Re-engineer and migrate existing applications to leverage scale and elasticity. Back in the data warehouse glory days, you only wanted to have the really important data immediately available, because you simply could not handle making all of the data persistent. It ended up though not being such a bad thing, because adding some governance to the process led to some discipline up front about what was more important and what was less important. True, technology limited storing ‘everything’ from a cost and capabilities perspective. The collective technology, which we might just call tools, really did not allow us to ‘have it all.’ Though many big data tools are open source, not all are created equal across cloud platforms. So what kind of skills should you bring on board to re-engineer existing applications? Many skills are transferable, so don’t decide solely based on your architects’ cloud platform religions as to whether you’ll be standing up AWS, Azure or Google Cloud.

Performance

Ensure SLA's through cloud infrastructure automation and orchestration. In ongoing cloud operations and performance, there is a need to process significant amount of data from web servers, application servers, databases and external sources. Whether on premise or off, you need to align the right set of skills when deploying big data in the cloud. Perhaps you’ll need experience in hosting and performance tuning to re-engineer product (machine) operations data for troubleshooting or analysis. Or maybe you’ll need knowledge in tools for load testing and log analysis as teams spin up thousands of servers across your cloud platform. SaaS experience should entail big queries on cloud services platforms. You’ll need to import data into the cloud storage and thereafter ingest to cloud storage from real-time sources. IaaS and PaaS experience should involve virtual machine, virtual network and tools heavy lifting on cloud platforms.

Optimization

Optimize workload performance to achieve operational excellence. Moving data in and out of cloud storage may end up being a blend of batch and real-time using cloud features such as Elasticsearch in an AWS cloud to search data lakes of mobile, social, consumer and business applications data. Alas, technology has advanced, and it is now cost effective to store gargantuan amounts of data – yes, unstructured too – in data lakes. The good news is, we get to store a bunch of data, but it requires a different type of optimization than the governance applied to data warehouses and data marts of days past. There is a need for real-time and near real-time visibility into operations. Basket analysis, for example, may use data ingested via a big data platform, where then custom programs do the analysis and prepare the results for reporting. Additionally, data may need to be correlated with other applications such as an Order Management System.