Providing Business Intelligence (BI) reporting and analysis used to be a service that IT provided for their line-of-business counterparts. In recent years, however business users have increasingly taken the lead for their BI and analytic solutions.
What’s Driving the Self-Service BI Growth Trend?
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Tags: analytics, Business Directory, business intelligence, Cisco Data virtualization, data virtualization
Forrester Consulting recently conducted a Total Economic Impact (TEI) study and examined the potential return on investment (ROI) enterprises may realize by deploying the Cisco Data Virtualization solution. This provides readers with a framework to evaluate the potential financial impact of investing in the Cisco Data Virtualization solution for their organizations.
Forrester gathered data through interviews with some of our long-term customers who have several years’ experience using the solution to better understand the benefits, costs, and risks associated with Cisco Data Virtualization. In this blog, I’d like to dive a little deeper on these customers, the challenges they were faced with and the results they are seeing from implementing Cisco Data Virtualization.
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Tags: Cisco Data virtualization, data integration, data virtualization, Forrester TEI Study, predictive analysis
At the recent Gartner BI Summit in Las Vegas, there was a lot of discussion about the paradigm shift underway in business intelligence (BI) and analytics. Business’s need for agile data access and self-service, combined with IT’s inability to satisfy this need, is causing disruption to traditional models and shifting the balance of power from IT to the business.
While that is certainly true, it is not a new phenomenon. In fact, it has been building for more than a decade.
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Tags: business intelligence, Cisco Data virtualization, data integration, data virtualization, software as a service
We’ve all heard the expression, “you can never have too much of a good thing.” But we all know that’s not quite true. For example, a little dessert is good. But too much can be a problem for your waistline.
It seems data marts also fit this pattern. A few data marts can be very helpful, but too many create a huge total cost of ownership (TCO) burden.
Fortunately, with data virtualization, you can turn physical data marts into virtual ones. And when you do, you will never have to worry about having too much of a good thing.
What’s Great about Data Marts
Data marts were developed as a complement to enterprise data warehouses. Typically subject or domain specific, and derivative of the warehouse, they provide a number of benefits including:
- Focused Content – Narrowing the scope to a specific domain such as finance or sales simplifies reporting and analysis.
- Query Performance – Offloading workload from the enterprise data warehouse can improve query performance.
- Data Structure – Certain reporting tools require certain structures, for example star schemas. Data marts can easily be modeled based on these structures as an alternative to the warehouse schema.
- Local Control – Users find it easier to control and modify data marts than larger warehouses.
Costs Can Outweigh the Benefits
Given the benefits cited above, data marts have proliferated rapidly. Unfortunately, as with deserts, “A moment on the lips can be a lifetime on the hips.” Data mart TCO is huge. Costs include:
- Development Costs – Each data mart requires a full design, development and deployment effort.
- Operating Costs – Not only does the data need to be refreshed regularly, all the underlying databases, database servers, ETLs and more must be monitored and tuned.
- Change Management Costs – Adding new data to respond to business change requires extensive rebuilding of complex data mart schemas and ETL scripts, adding costs and reducing agility.
- Data Governance and Quality Costs – Because data is physically replicated in each data mart, each mart requires data governance to ensure consistent quality.
Data Virtualization to the Rescue
As an alternative to physical data marts, many organizations now use data virtualization middleware such as the Cisco Data Virtualization Suite, to create virtual data marts. Virtual data marts provide all the benefits listed above with far lower costs.
- Development Costs – Virtual data marts have far fewer moving parts, which lessen design, development and deployment efforts.
- Operating Costs – Fewer moving parts also means less infrastructure to maintain.
- Change Management Costs – Adding new data to respond to business change can be done in minutes or hours via virtualized data sets, rather than days or weeks in the physical data mart world.
- Data Governance and Quality Costs – With data virtualization, data mart content can be centrally governed to ensure consistent quality wherever that data is used.
Try the Data Mart Diet
If you agree that it makes sense to lighten up on data marts, the question is how? In other words, what is the “Data Mart Diet?”
Fortunately Rick van der Lans, data virtualization’s leading independent analyst, has created the perfect Data Mart Diet program in his latest data virtualization white paper, “Migrating to Virtual Data Marts using Data Virtualization.”
This whitepaper include a step-by-step approach for migrating physical data marts to virtual data marts using Cisco Information Server. Steps include:
- Recreating Physical Data Marts as Virtual Data Marts
- Improving Query Performance on Virtual Data Marts
- Identifying Common Specifications Among Virtual Data Marts
- Redirecting Reports to Access Virtual Data Marts
- Extracting Definitions from the Reporting Tools
- Defining Security Rules
- Adding External Data to Virtual Data Marts
This guidance, along with the cost-benefit summary included at the start of the paper, make this paper a must read for organizations who are seeking a data mart diet.
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Learn More from My Colleagues
Check out the blogs of Mala Anand, Mike Flannagan and Nicola Villa to learn more.
Tags: agility, Cisco Data virtualization, data mart, data quality, data virtualization, virtual data mart
More data allows for better and more expansive analysis. And better analysis is a critical success factor for businesses today.
But most data warehouses use the once-in-never-out principle when storing data. So whenever new business activities occur, new data is added without removing old data to make room. New data sources, such as data from social media networks, open data sources, and public web services further expand the warehouse. Unfortunately, all this growth comes at a cost.
Is there a way you can have your cake and eat it too?
With Hadoop and Cisco Big Data Warehouse Expansion, you can.
Disadvantages of More Data
While everyone understands the business advantage that can be derived from analyzing more data, not everyone understands the disadvantages that can occur including:
- Expensive data storage: Data warehouse costs include hardware costs, management costs, and database server license fees. These grow in line with scale.
- Poor query performance: The bigger the database tables, the slower the queries.
- Poor loading performance: As tables grow, loading new data also slows down.
- Slow backup/recovery: The larger the database, the longer the backup and restore process.
- Expensive database administration: Larger databases require more database administration including tuning and optimizing the database server, the tables, the buffer, and so on.
Three Options to Control Costs
The easiest way to control data warehouse costs is to simply remove data, especially the less-frequently used or older data. But then this data can no longer be analyzed.
Another option is to move the lesser-used data to tape. This option provides cost savings, and in an emergency, the data can be reloaded from tape. But analysis has now become EXTREMELY difficult.
The third option is to offload lesser-used data to cheaper online data storage, with Hadoop the obvious choice. This provides a 10x cost savings over traditional databases, while retaining the online access required for analysis.
This is the “have your cake and eat it too” option.
The Fast Path to Transparent Offloading
Cisco provides a packaged solution called Cisco Big Data Warehouse Expansion, which includes the data virtualization software, hardware, and services required to accelerate all the activities involved in offloading data from a data warehouse to Hadoop.
And to help you understand how it works, Rick van der Lans, data virtualization’s leading independent analyst, recently wrote a step-by-step white paper, Transparently Offloading Data Warehouse Data to Hadoop using Data Virtualization, that explains everything you need to do.
Read The White Paper
Download Transparently Offloading Data Warehouse Data to Hadoop using Data Virtualization here.
To learn more about Cisco Data Virtualization, check out our page.
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Tags: Cisco Big Data Warehouse Expansion, Cisco Data virtualization, data analytics, data virtualization, Data Warehouse, Hadoop, rick van der lans