Components of Analytics Pricing
The following key components/heads of a Data Analytics Platform Implementation, at Enterprise Scale, when analytics is delivered to the entire ecosystem, will decide the TCO.
Cost head 1 [CH1] – Server Cost (Infrastructure Cost)
This is the cost of Servers on which the Data Analytics Platform Software will be installed and run, where Data Lake will persist, and Metadata Repository will stay
OR
OR
Cost Head 2 [CH2] – Cost of Data Analytics Software (Pure Play Licensing – User Licensing + Data Processing Charges + Compute Charges + Each Software basis there will be charges)
Data Pipeline | Data Quality | Data Catalog | Data as API | Data Virtualization | DevOps
Data Science Notebook | ML Compute Resources | ML Studio | ML Services | Model as API
Self Service | Search | Mobility | Visualization | Reporting | Data Sharing
To understand why CH2 gets unwieldy and expensive rather quickly for an enterprise-wide implementation for even a few hundred users, please have a read of a public URL https://azure.microsoft.com/en-in/pricing/#product-pricing. Most will quickly conclude that for just about every little tool or service, there is an additional charge, and it gets out of control rather quickly in only a few months of Production, when the data processing is not understood properly.
Cost Head 3 [CH3] – Cost of Data Lake (License + Internal hardware Usage + Support etc.)
AWS | Azure | GCP | Mongo (Atlas) | Click house | SQL Server | Oracle | MySQL | Hadoop | Snowflake, etc.
Any one of the above, or a combination thereof, can be the data lake. It can have a Raw Zone, Enriched Zone, Analytics Zone, and Consume Zone (or even more zones) based on Data Flow Architecture.
Some of the Data Lake architecture might involve more than one kind of system. It can involve multiple vendors as well.
Cost Head 4 [CH4] – Services or Consulting or Implementation Cost [Resource Cost]
Cost of Data Architects | Data Engineers | Data Scientists | Data Analysts | QA | Project Management | DevOps
Cost of Training, Certification, etc. for the above resources for every software an enterprise chooses
Location of the resource - Onsite | Offshore (India, etc.), as well as Consulting (Vendor) | Contractor | Customer Employee
Cost Head 5 [CH5] - Support | Training
Cost of DevOps Resources for Support | Cost of Service Resources for Support
Technical Support of the Product
Percentage of people required for the Support Vis-à-vis no of people required to build the solution (Important Metric)
Training Cost and time to get the Customer team trained on the product/Solution
Cost Head 6 [CH6] – Enhancement | Product Upgrade | Knowledge Management
Upgrade of Software Versions & their frequency
Cost of addition of a New Feature
QA cost & Migration Costs after Upgrades (whether Migration is seamless)
Flexibility & Custom Development Capability in the platform and cost to maintain and enhance the solution technically
TCO for an enterprise analytics platform implementation =
CH 1 + CH2 + …+ CH 6
+
Enterprise customer spends on program management & internal IT/Engineering Support (Requirements, Design, Review, UAT, Approvals, etc.)
+
Cost of Administration and Management (Finance/Legal/Executive etc.)
For most companies, it is difficult to estimate the expected TCO when the project starts, and the actual TCO often differs by 200% to 500% by the time the entire solution is up and running in Production (which btw is also delayed 90% time delayed due to various factors). One can imagine that this is a source of serious concern for the respective business, and the company leadership.
Let’s see how BDB fares in practice concerning all of these Cost Heads.
CH1 – Servers – BDB gives options to customers to use their Cloud/on-premises Infrastructure or use BDB’s infrastructure. We are always able to optimize this cost due to our Flagship Data Pipeline product.
CH2 – Software Licensing – BDB is possibly No. 1 in affordability of its licensing and this itself reduces TCO to a great extent. We don’t charge component by component, yet we are cost-effective as we give options to customers and partners in deciding.
Whether they want to take the User based pricing
Whether they want to take the Data consumption centric Core based pricing
Combination of 1 & 2 with Optimization of User Licensing for Visualization
Volume based Discounting
Please Note: BDB Charges 35 Cents per Core per hr for data processing, which is as good as processing 1 GB of data for 7 cents.
CH3 – Data Lake is sitting outside BDB platform, therefore it doesn’t directly impact our platform price, but we are able to execute in Data Lakes based on Click house or Mongo DB (Community Edition) just as effectively as other options, to help reduce customers TCO.
CH4 – A truly Unified platform (BDB) helps save in 4 key aspects.
The number of Roles or Skill sets required to implement Data Analytics using the BDB.ai platform is lesser, lessening the burden of staffing.
The total number of people required is 20-30% less (as compared to fragmented products or point solutions for the pipeline, data science).
Speed of implementation is often 3-5x faster than most competing options.
BDB Professional Service costs are often the lowest among enterprise product vendors, and their cost comparable to that of mid-tier system integrators.
CH5 – Due to the Integrated nature of the Platform and ease of use primarily via a simple drag-and-drop interface, we can provide comprehensive training to most resources in 2 months. Additionally, since Training is meant primarily as a customer enabler, our charges for these training activities are among the lowest in the industry (often 50-80% lower than some leading products)
BDB provides 24X7 support as premium support services. Our Support Charges are 10% lower than the Service Charges.
CH6 – BDB takes care of all logical Enhancements through its R&D team. And, BDB releases its product roadmap well in advance for Partners and Customers, thus enabling them to plan better.
For Customized Enhancements for Customers (Developer Rates), BDB charges 25% higher than the basic Service rates (implementation rates).
Please Note: BDB Claims to execute, maintain, support, and enhance any Data Analytics Implementation with 50-70% of TCO of any competition Globally.
When a Large Enterprise chooses to use BDB for its Data Monetization initiative, the above TCO reduces further & ROI is enhanced to the next level.
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