Cloud Providers
Contracts & Workload Management
AWS, Azure, GCP, IBM and Oracle are top U.S. cloud providers. These are "hyperscaler" clouds with AWS and Azure currently being the largest. They provide legacy Information technology (IT) services that scale and newer serverless solutions. Multi-cloud use is also increasing (both storage and compute). Selecting and optimizing IT services internally and among clouds is key. Our expertise and technical abilities provide business and IT assistance for internal, internal cloud and in-the-cloud services.
For cloud services, determining aggerate 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
Technology
Technology is the sum of techniques, skills, methods, and processes used in the production of goods or services or in the accomplishment of objectives, such as scientific investigation. - Wikipedia
Alexicon - areas to consider when analyzing and designing a single application or "service." Column on the left is your Company.
Company
Shareowners (Share Price and Total Shareholder Return (TSR)
Competitors
Short and Long term Objectives
Mission and Vision
Brand(s)
Products and Services
Strategic advantage(s)
Key Performance Indicators (KPIs)
Master Data Management and Transations
Targets and Results
Performance: Revenue, COGS, Expenses, Quality and Value
People
Talents and Skills
Relationships
Requirements, design, implementation and training
Understands and furthers processes
Helps design and define processes, systems, KPIs, indicators and reporting
Provides process and system training
Indicators and metrics
Goals and Targets
Motivated
Makes decisions
Change Management
Continuously improves processes
Process
Define, Measure, Analyze, Improve and Control
How things get accomplished
Embedded in systems, analytics and work instructions
System model and transformation process
Standardized process versus work-arounds (avoids two or more processes for same area)
Manual, Simi-automated and Automated
Dollars, counts and time durations
Guides consistent quantity and quality output
Systems
Internal and/or External
Users like the system
Meets the business process
Flexible for process improvements
Fosters involvement and use
Ability to transition to newer tools, methods and techniques
Avoids work-arounds
Highlights issues
Embeds business processes and workflows
Area analytics
Cost savings
Return on investment (ROI)
Where will the service reside?
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. The system in the middle is in-house and managed by a cloud partner.
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 20 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 intergraded 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.
With data models (data) associated well, IT spends most of their time building needed applications and analytics (avoids point-solutions, workarounds, duplication and unsureness). Main mission is to ensure accuracy, functionality, security and fast click times for users. Most systems are available or online 24/7. IT also needs to coordinate with all parts of the Company and with Suppliers across many systems.