What makes BDB delivering @40% TCO

Imagine the challenge of deploying an advanced analytics Customer Data Platform (CDP) for the retail division of a top-tier oil enterprise. This system must deliver business analytics to an impressive 50,000 users, with near real-time precision. Picture the complexity: integration of 8-10 varied data sources, blending streaming and near-real-time data, all orchestrated within the AWS ecosystem for a span of 3 years. The data footprint? Considerable, but manageable – a few hundred terabytes, even after data retention policies are applied.

Now, let's delve into the economics of such an undertaking on AWS. This isn't just about infrastructure; it's about adhering to stringent security protocols, setting up a licensed data lake, and ensuring a dedicated on-site team—comprising 20-30% of our workforce—collaborates closely with the customer.

Envision the AWS tools required to weave together a seamless CDP experience. We categorise our efforts into three segments

Tools of Data Analytics: (Segment A)

??????? AWS Lambda – Compute for Applications

??????? Sage Maker – Build, Train, Deploy ML Modes

??????? EMR – Spark Functions running on Large Data Framework

??????? AWS Glue – Data Integration and Preparation

??????? Amazon Neptune for Data Catalog & Lineage

??????? AWS Quick sight OR Tableau – for Visualisation with 50,000 Users

??????? Cloud Trail – Logging and Audit Services

Data Lake: S3, Aurora, RedShift etc.

Necessary Cloud Services: (Segment B)

??????? Base Servers to deploy and run the applications.

??????? Security – WAF/ Shield

??????? Load Balancer

??????? Network Cost of Ingress, Egress

??????? Multiple Allied Services of AWS – Charged separately for everything.

Team required to Deploy & Maintain Data Analytics (Segment C)

??????? Developers for Data Engineering with Skills on AWS

??????? Data Scientists for Machine Learning with Sage Maker

??????? Data Visualization Engineers

??????? DevOps Skills (AWS certified Cloud Engineers)

??????? Data Architects, Project Manager etc. – Every tool of AWS will demand a new skill to be recruited from market. You already know the price of a 3-5 yrs. Experienced engineer with these skills.

I have seen most of these proposals falls around 20m$ [for 4 years – 1 yr. deployment and 3 yr. maintenance with support. This is for an enterprise in India.

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Now let’s consider an environment with AWS and BDB, these 3 segments are –

Segment A – BDB deployed on AWS (it has following Data Analytics Features built in) [Cost is BDB Licenses here]

??????? Data Ingestion and Orchestration – ETL, ELT

??????? Data Catalog, Data Lineage

??????? Serverless Deployment of Jobs

??????? Data Science Lab for Build, Train, Deploy ML Models

??????? Data Virtualization Layer to Optimally use Analyzed Data

??????? Data Visualization with Self Service and Dashboards

Data Lake: Keep the same as mandated by Customer.

Segment B – Remains same as mandated by Customer.

Segment C:

§? 90% BDB Skills & 10% AWS Skills

§? Average cost of BDB Skills in India is 30% Lower than AWS Skills

§? Average no of resources required to build and maintain a large deployment in BDB is 30-35% of pure AWS.

§? Due to Integrated nature of the platform

§? Only SQL and Python skills required to use BDB.

§? BDB is a true LOW CODE Platform for data professionals.

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BDBs proposal for the same is 8 m$ (agreeing to all T&C of Enterprise) where Enterprise can use BDBs team for Implementation & Support.

In case some customers want to use our partners or SI of their choice, that is also possible.

?From where TCO is reducing so drastically?

1.???? Difference in Licensing – BDBs licensing is optimized.

2.???? Implementation with a smaller team as the platform is integrated.

3.???? Cost of Training and Resource is further optimized.

Now let’s say customer want the implementation on Azure or GCP than similar concept is applied and BDB product will be able to do the work of following products –

Azure: (Segment A)

??????? Azure Functions – Compute for Applications

??????? Machine Learning Service – Build, Train, Deploy ML Modes

??????? Databricks / HDInsight? – Spark Functions running on Large Data Framework

??????? Azure Data Factory – Data Integration and Preparation, ETL

??????? Azure Data Catalog & Lineage

??????? Power BI – Powerful Visualization Tool

??????? Log Analytics – Logging and Audit Services

Data Lake: Azure Data Lake and other Database variants

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GCP: (Segment A)

??????? Google Cloud Functions – Compute for Applications

??????? AI Platform– Build, Train, Deploy ML Modes

??????? Dataproc – Spark Functions running on Large Data Framework

??????? Cloud Dataprep – Data Integration and Preparation

??????? Google Cloud Data Catalog

??????? Looker – Acquired Product not integrated properly

??????? Logs Explorer– Logging and Audit Services

Data Lake: Big Query and other database variants

The journey of discovery begins with that first conversation, and we know our initial impression often seems too remarkable to be true. Yet, when our customers dive into a use case, they don't just take our word for it—they measure and experience the exceptional speed and quality firsthand.

In an industry where the debate between price and functionality rages on, we stand by a simple truth: even the largest brands started small, and pricing isn't just a detail—it's a pivotal factor for ethically-run businesses. This is why the 'Pricing' page is so often the next stop after 'What We Do'—because while the value is paramount, cost efficiency is a universal priority.

BDB has been meticulously crafted over ten years by BI specialists, with a singular vision: to empower businesses with accessible data analytics. As a self-funded platform, we operate on lean margins, focusing on delivering quality without the frills of unnecessary freebies.

Excitingly, BDB is now opening doors wider with the launch of our SaaS offerings, designed to present compelling options for businesses of every size. We invite you to explore these opportunities at BDB SaaS Platform.

Stay tuned for my next piece where I'll delve into a use case for building a CDP for 1 million subscribers, and unravel the cost benefits of choosing BDB's SaaS, Private Cloud, or On-Premises solutions.

Join us, and let's redefine the value of data analytics together.