Cloud Providers

Contracts & Workload Management

AWS, Azure, GCP, IBM and Oracle are top U.S. cloud providers. These are "hyperscaler" clouds with AWS, Azure and Google currently being the largest. They provide legacy Information technology (IT) services that scale and newer serverless solutions. Major uses are Virtual Machines (VMs) and Hyperscale for large data processing. Multi-cloud use is also increasing (both compute and storage). Selecting and optimizing IT services internally and among clouds is key. Dell VxRail/VMWare Horizon hyper converged infrastructure (HCI) systems are now gaining popularity for In-house Clouds. Our expertise and technical abilities provide business and IT assistance for in-house and cloud services. Many Enterprise software applications are moving to the cloud, as well as, Enterprise Data Warehouses (EDWs).

For cloud services, determining aggregate spend, service performance and proactively making service changes can be a challenge to manage. Also, making a choice to build in-house, cloud on-premise or in-the-cloud.

Workload Management

Manual and automated workloads

Applications, Installs, Updates, Monitoring, VMs, Containers, ETL, SQL and serverless use

System prototype testing (reliability, speed and use)
Price Plans
Price Cost Analysis
Reserved Services (plan ahead)
Portability Testing (switching a service or provider)
Label or ID Services for reporting
Allocate Services to departments or organizations
Monitor supplier Service recommendations
Optimize Services and spend continuously

Adjust, add or remove service

Multi-cloud use

Avoid unexpected high bills when using cloud services by planning, budgeting, allocating, monitoring and optimizing performance and spend. Proactive self-management. Change services when needed.

Microsoft, Google, Amazon Web Services and IBM are leaders in Gartner's 2021 Magic Quadrant for Cloud AI Developer Services

Service

Below are systems that provide a service. Servers can be added physically or virtually to scale (cloud advantage). Commodity servers are used in cloud data centers to reduce hardware costs.

Enterprise Data

Most companies are moving rapidly toward improved application integration, reporting and working on their enterprise data warehouses (EDWs). Visualizations, dashboards and reports “report” data. They all require a grid(s) or chunk-like datasets (smaller the better). Advanced data modeling is a highly-valuable area (a Company’s association model). It is where all the pieces come together for an enterprise data model with fully-managed master data.

The better the enterprise data model, the fewer applications, visualizations, dashboards and reports (consolidation and standardization). We have worked in environments where tens of thousands of reports exist because of natural EDW growth (adding data sources, dimensions and facts). Evolves overtime.

Accelerated help

Your advantage with Alexicon assisting is 23 years of experience with strategic data models. We mentioned a few years back the connection with multidimensional data models and high-dimensional statics. A fully integrated EDW provides a Company’s Multidimensional Data Model to perform Multi-dimensional Statistics. It has all possible dimensions and facts needed to perform data science computations. A structured data warehouse can drill from the top to needed levels quickly and with accuracy. The same drilling is needed for High-dimensional statistics and other data science computations. For EDWs, users should never experience inaccuracy (1 + 1 = 2.01) when using a system.

Enterprise. Orchestrated.

Enterprise Operating System (EOS)

Enterprise Resource Planning (ERP) and surrounding systems: Customer Relationship Management (CRM), Supply Chain Management (SCM), Human Resources Management System (HRMS), Information Technology Service Management (ITSM), other COTS and In-house Built Applications.

Integrated Applications and Analytics.

In-house and Cloud Planning, Migrations and System Operations.

Process focused Work Instructions.

Leverage a Data Dictionary and "Metadata" for the Enterprise to assist with planning software applications and the data landscape.