IT Category Purchasing Managers Opportunity for Savings with Non Relational Systems such as Hadoop
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Open Source Non Relational Storage Systems A Strategic Cost Savings Opportunity for Purchasing IT Category Managers Bill Kohnen IT Procurement Forum Discussion San Francisco CA
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Non relational data approaches applied effective can result in massive cost reduction and performance improvement compared to an infrastructure of legacy enterprise hardware and software solutions. While still not totally without risk on an enterprise scale some tech savy early adopters are realizing tens of millions of dollars in total cost savings. Astute Corporate IT Buyers should include this on their roadmaps if for nothing else to leverage Legacy IT providers
Transcript of IT Category Purchasing Managers Opportunity for Savings with Non Relational Systems such as Hadoop
Open Source Non Relational Storage Systems
A Strategic Cost Savings Opportunity for Purchasing IT Category Managers
Bill Kohnen IT Procurement Forum Discussion
San Francisco CA
With growing volumes of data and increasing requirements to process and analyze data even faster, organizations are faced with several options:
1. To add more hardware and/or horsepower to their existing infrastructure and operational systems. Very expensive and especially with legacy hardware and ERP providers (HP, Cisco, EMC, Oracle, SAP etc.) Also performance only scales but does not improve
2. Consider alternative ways to manage their data.
3. Do nothing. Organizations must ask themselves is all data important and should they try to capture all of it to process, analyze and discover greater insights in it?
Benefits of using Open Source Non Relational Storage Systems
• Open source software - Lowers Cost
• Running on commodity hardware Lowers Cost
• Performance is better than that of traditional databases
• Decades of data can now be stored more easily and cost-effectively.
• Data does not need to be destroyed after its regulatory life to save on storage
• Analysis can be conducted on larger set of data
Cost Savings
• Hardware 60%• Development 30%• Other software 50% (ETL, Enterprise BI
solutions) • Enterprise Software Maintenance 100% for
some applications• Enterprise Hardware Maintenance 80%
Even Mid Sized Companies Can Save Millions over several years.The most aggressive early adopters like Facebook have saved hundreds of millions combined total cost.
Enterprise Data Warehouse (EDW) - Simplified, Traditional setup:
Structured Data
Enterprise Data
Warehouse
BI Analytics
Open Source Non Relational File System - Simplified setup:
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
Typically Run Parallel
Structured Data
Enterprise Data
Warehouse
BI Analytics
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
Ways to Shift the Current Corporate Data Paradigm with Open Source Non Relational Systems such as Hadoop
• Stage structured data• Process structured data• Process non-integrated & unstructured data• Archive all data• Access all data via the EDW• Access all data via Hadoop
Stage Structured Data
Structured Data
Enterprise Data
Warehouse
BI Analytics
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
Reduces Storage Costs, Frees Enterprise Processing Power, and de bottlenecks ETL
Process Structured Data
Structured Data
Enterprise Data
Warehouse
BI Analytics
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
Reduces Storage Costs, Frees Enterprise Processing Power, and de bottlenecks ETL Even if you do not currently have massive big data sources
Process non-integrated & unstructured data
Structured Data
Enterprise Data
Warehouse
BI Analytics
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
Reduces Storage Costs, Frees Enterprise Processing Power, and de bottlenecks ETL When you say all data is important but want it available in both systems
Archive All Data
Structured Data
Enterprise Data
Warehouse
BI Analytics
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
Eliminates need to Purge Data so can Analyze Big Sets of Data
Access all data via the EDW
Structured Data
Enterprise Data
Warehouse
BI Analytics
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
More Cost Effective way of maintaining Legacy System as “system of record”
Access all data via Non Relational Database such as Hadoop
Structured Data
Enterprise Data
Warehouse
BI Analytics
Un Structured
Data
Open Source Non
Relational File System
Big Data APs
Paradigm Shifting Approach
Summary
• IT Category Managers should work with corporate IT to evaluate potential incorporation of non relational database approaches as a major cost and performance improvement
• There are still near term risks as the technology on an enterprise scale is still maturing
• A major threat to Legacy hardware and software providers and even new BI tool market
