Journey to Cloud Analytics

Editor's Notes

• #6: This is not a “niche” solution – this is the future of how companies will achieve Strategic Agility and Differentiation. Why do we get deals or credits from AWS and Azure? Because they can’t keep up with the demand – they need companies like Datavail! Should Datavail focus on any particular area within that market?” Answer: Yes, the Cloud area of Big Data and Business Analytics Solutions. Cloud Analytics growing from 52 Billion this year to 121 Billion in 2022
• #7: The lack of innovation is not the result of laziness. People and organizations are simply too busy providing descriptive analytics to engage in in-depth thinking. Simply migrating to the cloud with a “lift and shift”' approach does not result in innovation, but it does add another level of complexity to operations. The effort expended on maintaining the traditional analytics process turns into “analytics debt” for organizations, which impedes their ability to be creative and innovative. This lack of innovation ultimately costs organizations in terms of productivity in analytics, preventing them from adding value to the business. It is urgent, therefore, for organizations to explore the cloud, and inevitable that they will do so, as this is where new capabilities emerge owing to the effects of data gravity
• #9: Cloud analytics offers new capabilities for users to generate business value through a trial-and-errorbased environment. Organizations can introduce cloud analytics as a use case for users to generate more visible analytics prototypes that form the basis for innovation (see Figure 3). Data and analytics leaders need to pitch onboarding with cloud analytics as an ideation process to start analytics with the following steps.
• #10: Note: This is mostly business needs, not an IT needs! IT should know this, but often don’t. Basically they want answers to business questions – when they want to ask them – not all up front in a “requirements gathering” phase. Scalable – don’t want to wait for a procurement process…. Hopefully, Modern Analytics addresses many of these needs.
• #19: Needed to rearchitect using new technologies and approaches.
• #20: What’s different about this solution? Serverless. Less delivery of data sets and more interaction, ad-hoc analyses by both internal and external users. Delivers Business Insights more than data sets. Very elegant solution!
• #23: Stan Add bullets about flexible data ecosystem that enables them to adjust and change to meet their business objectives. Add more content and bullet points about this. Cloud on demand Agility of the business Infrastructure flexibility – Cloud Future demands Real time reporting and inventory management Quality of the solution – flexibility and quality Time to delivery of changes to meet the reporting needs as they change The solution must provide the ability to re-develop the existing process while providing a capability for managing services for processing data from over 75,000 chains and 15,000 wholesalers and consolidating with master data (Store, SAP Customer, Product, Employee pro) to create cubes in SQL Server. These cubes will be consumed by over 30 analysts/data scientists and the resulting output (reports, dashboards) are viewed by over 300 users and must provide like functionality as to what the analysts/data scientists leverage today. Scope   The overall scope of the solution is to process data from the existing data sources and to then create data cubes for analysis. Data for processing the RBH data received from the following sources:   75000 + stores  15000+ wholesalers    The Master data that must be leveraged in the processing of the data received from these sources includes the following master data: Store   SAP Customer   Product   Employee     There are two File Specs expected for the Chains, however there are up to 5 different formats between 30 participating chains. Some chains will submit weekly aggregated data and the remaining chains will submit data at the daily aggregate level, but it will be submitted weekly. Some chains will be providing data in the Excel format and the remaining chains will be providing data in the text file format.     The structure of the input data files from the store chains, wholesalers and master data will be provided by RBH or RBH will designate the service provider as the party that is authorized to communicate directly with the wholesalers and store chains to acquire the input data file structures.     The overall solution must be responsible for keeping track of receiving the input files from the wholesalers, store chains and maser data from RBH. Vendor will also be responsible for following up with the input file and master data providers in case of any delay in receiving these files. The overall solution must be authorized by RBH to communicate with the wholesalers and store chains on behalf of RBH.    The logic to perform the ETL process to transform the input files form the wholesalers and store chains into an output format that can be used by RBH analysts to execute existing reports, dashboards or ad hoc queries will be developed for use by the existing team of analysts/data scientists in a format similar to what they are using today. This format will be provided by RBH as well as the requirements for the overall process including any transformation business rules are not clear from the output format like in the case of calculated fields.  The new process must also be designed and developed to cleanse and consolidate points of sales data for the products that are not present in the RBH master file. 
• #24: Stan
• #34: A little like switching from film pictures to digital pictures. Answers the question, Who Needs Modern Analytics? Pretty much everyone. Cloud analytics lets companies leverage the power of analytics more quickly, more powerfully, and at lower cost. Cost Savings: Cost savings or financial benefits are one common reason for moving to the cloud. If you are only looking to just move your spending from a capital expense model to an operational expense model, then your achievement criterion is effortlessly met by simply moving to the cloud and subscribing to “as a service.” Agility: Another major reason for moving to the cloud is agility, but this is an option only if agility is important to you. For example, when on-premises capacity is made to handle the main jobs of the month, quarter, or year, then moving resources to the cloud can allow you to right-size the on-premises infrastructure for the workloads it needs to handle most of the time and only raise up to the peak demand when needed.
• #35: A little like switching from film pictures to digital pictures. Answers the question, Who Needs Modern Analytics? Pretty much everyone. Cloud analytics lets companies leverage the power of analytics more quickly, more powerfully, and at lower cost. Cost Savings: Cost savings or financial benefits are one common reason for moving to the cloud. If you are only looking to just move your spending from a capital expense model to an operational expense model, then your achievement criterion is effortlessly met by simply moving to the cloud and subscribing to “as a service.” Agility: Another major reason for moving to the cloud is agility, but this is an option only if agility is important to you. For example, when on-premises capacity is made to handle the main jobs of the month, quarter, or year, then moving resources to the cloud can allow you to right-size the on-premises infrastructure for the workloads it needs to handle most of the time and only raise up to the peak demand when needed.