Is Your Data Center Ready for Big Data?€¦ · Informatica PowerPoint Template Author: Informatica...
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1 Is Your Data Center Ready for Big Data? Julie Lockner VP, ILM Business Unit
Transcript of Is Your Data Center Ready for Big Data?€¦ · Informatica PowerPoint Template Author: Informatica...
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Is Your Data Center Ready for Big Data?
Julie Lockner
VP, ILM Business Unit
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Top Initiatives Influencing IT Purchases
3. Maintain Security & Compliance
2. Reduce Cost
1. Improve Business Process Efficiencies
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Enhancing Analytics Is Among The Top 5 Priorities
© 2012 Enterprise Strategy Group
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What Does “Big Data” Mean To You?
© 2012 Enterprise Strategy Group
11%
15%
17%
19%
21%
30%
42%
59%
0% 20% 40% 60% 80%
Hadoop / MapReduce
Web log and search engine data
Inability to store, process, and analyze large data sets
Scale-out storage
Complex data analytics
Enterprise data warehouses
Very large databases
Very large data sets
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Largest Data Set Processing / Analytics Challenges
© 2012 Enterprise Strategy Group
9%
16%
16%
20%
20%
21%
22%
24%
25%
27%
28%
29%
30%
34%
0% 10% 20% 30% 40%
Data center floor space costs
Database software license costs
Data analytics application software license costs
Data governance
Data set sizes
Lack of skills
Master data management
Storage costs
Data synchronization
Business’ expectations on how long it takes for tasks to complete
Data cleansing tasks
Data quality
Data integration
Data security
What are the most significant data processing and analytics challenges your organization faces with its largest data set? (Percent of respondents, N=399, multiple responses accepted)
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When Is Data Considered Big?
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What Is Stopping You From Going Bigger?
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Evolution in Big Data Analytics Platforms
Analytical DB Hadoop
OLTP
OLTP
EDW
Data Mart
Analytics
ODS
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Current Deployed Data Analytics Platforms
© 2012 Enterprise Strategy Group
Custom-developed solution, 31%
General purpose distributed computing
environment, 15% SMP (symmetric multi-
processing) general purpose database, 14%
Workload-specific appliance, 12%
Public cloud-based platform (i.e., SaaS,
PaaS), 10%
MPP (massively parallel processing) analytical
database, 7%
MapReduce (e.g., Apache/Hadoop
cluster), 2%
Other, 1%
Don’t know, 8%
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Plans For New Analytics Platform In the Next 12-18 Months
© 2012 Enterprise Strategy Group
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Current & Preferred Infrastructure for Data Analytics
© 2012 Enterprise Strategy Group
Do It Yourself Reference
Architecture
Fully Integrated
Solution Don’t Know
12
Interest In MapReduce
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