Big Data Procurement Intelligence

In this big data procurement intelligence report, we have estimated the pricing of the key cost components. The cost of big data development can vary significantly depending on the project scope, data volume, technology stack, and other factors. Organizations should carefully analyze their specific requirements and evaluate the potential return on investment before embarking on a big data initiative. The major cost components of big data development include system development and integration, testing and launch, maintenance, architecture design, hardware and software configuration and others. The implementation of big data solutions can be costly, with costs ranging from USD 200,000 to USD 3 million for a mid-sized organization. However, the benefits of big data can also be significant, including the ability to make better decisions, improve operational efficiency, and gain a competitive advantage.

For instance, Amazon conducted a study on the costs associated with building and maintaining data warehouses, finding that the annual expenses can range from USD 19,000 to USD 25,000 per terabyte. This means that a data warehouse containing 40 terabytes of information (a modest repository for many large enterprises) would require an annual budget of approximately USD 880,000 (close to USD 1 million), assuming that each terabyte requires USD 22,000 in upkeep. 

Order your copy of the Big Data category procurement intelligence report 2023-2030, published by Grand View Research, to get more details regarding day one, quick wins, portfolio analysis, key negotiation strategies of key suppliers, and low-cost/best-cost sourcing analysis

Operational Capabilities - Big Data

  • Industries Served - 25%
  • Years in Service - 15%
  • Revenue Generated - 15%
  • Employee Strength - 15%
  • Geographic Service Provision - 10%
  • Certifications - 10%
  • Key Clients - 10%

Functional Capabilities - Big Data

  • Statistics - 30%
  • Spatial analysis - 25%
  • Semantics - 15%
  • Interactive discovery - 15%
  • Visualization and others - 15%

Rate Benchmarking

The geographical location and nature of the business play a vital factor in analyzing the rate benchmarking of big data category. For example, big data services in the U.S. are typically more expensive than services in India. For instance, Oracle Big Data Service (OBDA) is a cloud-based platform offering data storage, processing, and analytics. Its pay-as-you-go model starts at USD 0.0319 per vCPU per hour, influenced by skilled labor availability and regulatory environment. The cost of big data services varies depending on the scale of the project. 

For example, a small business that is simply looking to implement a big data-based solution will likely pay less than a large enterprise that is looking to build a bigger big data-based platform. Smaller big data-based applications will be less expensive to develop and maintain than larger applications. This is because smaller applications will require less data storage, processing power, and analysis. Additionally, the cost of labor will be lower for smaller applications, as there will be fewer developers and analysts required to build and maintain the application.

Supplier Newsletter

In January 2023, Google Cloud announced that it had acquired Cerebras Systems, a leading provider of wafer-scale AI chips. This acquisition will allow Google Cloud to offer customers more powerful and scalable AI solutions by expanding its AI capabilities. Cerebras Systems' wafer-scale AI chips can process massive amounts of data at high speeds. This will allow Google Cloud to provide customers with AI solutions that are more powerful and scalable than ever before.

In December 2022, Microsoft announced that it had acquired Databricks, a leading provider of cloud-based data analytics platforms. This acquisition will enable Microsoft to provide customers with a more comprehensive big data platform by augmenting its big data analytics capabilities. Databricks and its acquisition will give Microsoft a significant foothold in the big data analytics market. The acquisition will also allow Microsoft to offer customers a more integrated platform for data analytics, from data ingestion to machine learning.

In November 2022, IBM announced that it had acquired Databand.ai, a leading provider of data observability solutions. IBM will be able to provide customers with a more comprehensive data observability platform as a result to this acquisition, which will increase its data reliability capabilities. Databand.ai's platform helps businesses track the health of their data pipelines and identify issues early on, before they cause problems. This will give IBM customers a significant advantage in terms of data quality and reliability.

In October 2022, AWS announced that it had acquired Sensalytics, a leading provider of IoT data analytics solutions. By enhancing its IoT data analytics capabilities, this acquisition will enable AWS to provide customers with a more complete IoT data analytics platform. Sensalytics' platform helps businesses collect, analyze, and visualize data from IoT devices. This will give AWS customers a significant advantage in terms of understanding and acting on data from their IoT devices.

List of Key Suppliers

  • Accenture
  • Cloudera
  • Google
  • Hewlett-Packard Company
  • IBM
  • Mu Sigma Inc.
  • Amazon
  • Oracle Corporation
  • Splunk Inc
  • Teradata Corporation 

Browse through Grand View Research’s collection of procurement intelligence studies: 

Big Data Procurement Intelligence Report Scope 

  • Big Data Category Growth Rate : CAGR of 12.7% from 2023 to 2030 
  • Pricing Growth Outlook : 3% - 4% (Annually) 
  • Pricing Models : Subscription-based 
  • Supplier Selection Scope : Cost and pricing, past engagements, productivity, geographical presence 
  • Supplier Selection Criteria : Type, technical expertise, security measures, support and maintenance, cost-effectiveness, and others 
  • Report Coverage : Revenue forecast, supplier ranking, supplier positioning matrix, emerging technology, pricing models, cost structure, competitive landscape, growth factors, trends, engagement, and operating model 

Brief about Pipeline by Grand View Research:

A smart and effective supply chain is essential for growth in any organization. Pipeline division at Grand View Research provides detailed insights on every aspect of supply chain, which helps in efficient procurement decisions. 

Our services include (not limited to): 

  • Market Intelligence involving – market size and forecast, growth factors, and driving trends
  • Price and Cost Intelligence – pricing models adopted for the category, total cost of ownerships
  • Supplier Intelligence – rich insight on supplier landscape, and identifies suppliers who are dominating, emerging, lounging, and specializing
  • Sourcing / Procurement Intelligence – best practices followed in the industry, identifying standard KPIs and SLAs, peer analysis, negotiation strategies to be utilized with the suppliers, and best suited countries for sourcing to minimize supply chain disruptions