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May 24, 2010
Top 10 Technical requirements for In-Memory Reporting
With Gartner's Business Intelligence group listing In-Memory analytics at the top of their recommended Business Intelligence requirements for enterprise; No wonder In-memory has become a trending topic in BI and a new addition to executive shopping lists.
We thought we’d share with you our top 10 technical requirements, you should be asking from an in-memory analytics vendor:
[10] Data security must be of paramount concern
In memory applications have the potential to expose significantly more data to end-users then ever before. This raises security issues regarding how data is accessed, where it is stored and who has access to that data.
In determining the best strategy for your in-memory deployment, security needs to be foremost in your selection criteria. There are two aspects of security. Firstly, where is your data stored and is that storage secure? And secondly, who has access to that data store? Transactional applications go to great lengths to embed data security and access rules – ensure your in-memory database inherits these and is not simply a data access free for all.
[9] Ensure real time data refresh - incrementally loaded
Because reporting data is extracted from a source system or a data warehouse and then loaded into memory, data latency can be a concern. Front-line workers in a customer service centre, for example, need near-real-time highly granular (detailed) data. If an in-memory tool contains last week’s product inventory data, it’s probably not of use to customer service reps. Thus, the suitability of an in-memory tool and the success of the deployment may hinge on the degree to which the solution can automate scheduled incremental data loads.
[8] Server side rather than Client side
Consider a scenario where users are able to conduct complex queries by downloading up to 100 million rows of data to their desktop from many data sources, or data feeds from the web. Sure the information can then be sliced and diced into reports or users can create BI applications on their desktops and share them with colleagues. This sounds great in theory but is fraught with danger in practice. Not only does this have a massive potential to create data silos but with this level of data stored on a laptop, it is free to leave your premises and get lost or stolen in the worst case or published without any form of governance at best.
[7] Web-based GUI development and deployment.
Some in-memory tools are not nearly as web enabled as their conventional BI counterparts. This seems to reflect both technology immaturity and a tendency to be a niche deployment. However, for successful adoption with minimal administrative overhead web based development and deployment is critical. Both the visualization tool and in-memory database need to be server based deployments to ensure that data access security and application upgrades can be easily managed. Solutions such as Yellowfin provide a single web based platform for delivering your Business Intelligence needs. From connection through to design, modeling and visualization, your users work within a fully integrated browser application that encourages collaboration and an iterative approach to report development - leading to analytical applications that meet the needs of your end users.
[6] Integration with your existing data warehouse and OLAP cubes
While some vendors tout in-memory as a way of avoiding building a data warehouse, this option usually applies to smaller organizations that may only have a single source system. For larger companies that have multiple source systems, the data warehouse continues to be the ideal place to transform, model and cleanse the data for analysis.
Look for tools that are designed to integrate with and leverage existing BI environments. An in-memory solution that is tightly integrated into the visualization tool is critical. However, it is equally important that the visualization tool can also access your OLAP cubes and data warehouse tables without the need for an in-memory middle-layer. Without this option a purely stand-alone in-memory solution can lead to yet another version of the truth, adding complexity to your BI environment.
[5] Data Serialized to disk to enable rapid recovery
An image of the in-memory database is saved to disk, allowing the system to quickly reload the image should the system need to be restarted. This means that data can be loaded into your in-memory database without the need to place additional strain on your production or transactional servers.
[4] Platform independent
It’s important when selecting an in-memory database that it be platform independent. It should run on any hardware platform (PC, Mac, SunSparc, etc.) or software platform (Linux, MacOS, Unix, Windows, etc.).
[3] Enterprise scalability
It is critical to select enterprise class infrastructure that enables you to scale your deployment as your users grow.
All BI solutions must include enterprise administrative features, such as usage monitoring, single sign-on and change management; and this is just as true for in-memory solutions. It is therefore, critical that you choose solutions that can provide enterprise class infrastructure that enable you to scale your deployment as your users grow.
[2] Minimal administration overhead
In-memory analytic tools often introduce some of the same concerns that OLAP stores create: namely, they usually create another data source, with its own calculations and business definitions. This is where tools such as Yellowfin differ from other in-memory approaches: existing queries, reports and dashboards automatically take advantage of an in-memory database, seamless to users. Administrators are not adding calculations and business logic within another layer; they reside within the existing meta-data layer for reporting that is already built.
[1] Be open - allow other applications to connect to it (other than the in-memory database provider)
It’s important to source a non-proprietary database, in-memory databases are usually bundled with a visualization tool and it’s important that the provider allows other tools to connect to the database so that you can maximize your investment in the technology, rather than being tied to a proprietary solution.
Further Information:
Download publications (Click Link or Cut into Browser, No signup or Email required)
In-Memory Brochure
http://yellowfin.com.au/Document.i4?DocumentId=104877
In-Memory Whitepaper
http://yellowfin.com.au/Document.i4?DocumentId=104879
About Yellowfin
Yellowfin is passionate about making Business Intelligence easy. Recently recognized among 25 rising companies that CIOs must know about, Yellowfin is a leading web-based BI solution that can be easily integrated into any third-party application or delivered as a stand-alone enterprise platform. Yellowfin is an innovative, fast and flexible solution for reporting and analytics, providing a full range of data access, presentation and information delivery capabilities. www.yellowfin.bi
For further information / interviews please contact:
Catriona McGauchie
Marketing & Communications Manager, Yellowfin
Direct line: 61 3 9090 0454 Mobile: 61 (0)428 368 371 Email: catriona.mcgauchie@yellowfin.bi
Posted by Justin Hewitt at 5:45 AM | Comments (1)
May 13, 2010
Yellowfin delivers Fast Deployment and even Faster Analytics
Yellowfin, a leading Business Intelligence company announces the release of 5.0. This milestone release incorporates features that will enable rapid deployment and analysis such as in-memory analysis and excel spreadsheets as a data source. From a geo-spatial perspective, Yellowfin will also incorporate the ability for users to do advanced spatial filtering for location intelligence as well.
The result is that Yellowfin is not only making Business Intelligence easy but fast as well. With Yellowfin’s in-memory database queries will be lighting fast, and the ability to deploy even faster. Three simple steps are all that it takes to connect to your data source, map your data and then visualize.
Today's BI applications must efficiently access terabytes and even petabytes of data. Since most competing BI tools do not include performance acceleration engines, average BI application query response times often range from 10 seconds to one minute or more. Yellowfin’s
In-memory database has been setting some very fast times in its Beta testing, aiming to deliver up to 10x faster query response time at any data scale.
Its fair to say that the addition of in-memory technology is not a pioneering move for Yellowfin, as companies including QlikTech, Spotfire (now a part of TIBCO) and Applix TM1 (now a part of IBM Cognos) have had it for years. However Yellowfin’s integrated In-memory technology takes advantage of hardware-based memory and multi-core processors to turbo charge queries and ease data exploration while also eliminating IT data-prep work such as cube building.
At this year’s Gartner BI Summit, the business intelligence group advised enterprises to keep an eye on emerging BI technology areas. It is said that many of the executives attending this years Summit were intrigued by this proposed new world BI order, which includes:
* In-memory analytics
* Cloud-based services
* Columnar databases
* Interactive visualization reports
* Mobile BI applications
Yellowfin 5.0 allows executives to tick off all items on the Gartner checklist that they would be looking for in a leading web-based solution and with Yellowfin 5.0 everything is integrated, seamlessly, there is no need to move between multiple applications. Not only does this provide end users with a greater experience but also it makes it cheaper to roll out in mass deployments, which Yellowfin specialises in.
Fast analysis, better insight and rapid deployment with minimal IT involvement. These are the leading benefits of in-memory analytics. With Yellowfin 5.0, In-memory analytics delivers decision insight with the agility that businesses demand. It’s a win for business users, who gain self-service analysis capabilities, and for IT departments, which can spend far less time on query analysis, cube building, aggregate table design, and other time- consuming performance-tuning tasks.
Yellowfin 5.0 is making Business Intelligence faster and even easier. Click to view on-demand webinar of the official launch of Yellowfin 5.0
Ends
About Yellowfin
Yellowfin is passionate about making Business Intelligence easy. Recently recognized among 25 rising companies that CIOs must know about, Yellowfin is a leading web-based BI solution that can be easily integrated into any third-party application or delivered as a stand-alone enterprise platform. Yellowfin is an innovative, fast and flexible solution for reporting and analytics, providing a full range of data access, presentation and information delivery capabilities. www.yellowfin.bi
For further information / interviews contact: Catriona McGauchie, Yellowfin, Mobile: 61 (0)428 368 371
Posted by Justin Hewitt at 5:45 AM | Comments (0)
May 12, 2010
Selection criteria for an in-memory analysis solution
The evolution of reporting and analytics has seen dramatic changes in recent years. Starting with static “green bar” reports in the mid-to-late '70s, information could be abstracted from mainframe systems and, often manually, transferred to spreadsheets where data could be aggregated and analyzed. Data warehousing was the buzz of the '80s, and while this did enable heterogeneous data sources to be centralized, projects were often grossly over budget and far below expectations. As technologies have matured and the advent of services-based architectures has become more prominent, data warehousing reinvented itself and emerged as what is now recognized as business intelligence.
However, the recent advent of in-memory analysis means that Business Intelligence expectations have changed forever. Dealing with overly complex software designed for a handful of power users involving long deployment cycles and low project success rates is no longer acceptable. Today, smart companies are striving to spread fact-based decision making throughout the organization, but they know they can’t do it with expensive, hard-to-use tools that require extensive IT hand holding. The pace of business now demands fast access to information and easy analysis; if the tools aren’t fast and easy, business intelligence will continue to have modest impact, primarily with experts who have no alternative but to wait for an answer to a slow query.
The success or failure of in-memory analysis does, however rest to some degree on the technology chosen to be the delivery platform. The fundamental requirement is that this platform is web-centric, beyond that there are some essential technology components that assist to deliver the business benefits sought. These are:
Enterprise scalability and security
All BI solutions must include enterprise administrative features, such as usage monitoring, single sign-on and change management; and this is just as true for in-memory solutions. It is therefore, critical that you choose solutions such as Yellowfin business intelligence, with its integrated in-memory database, that can provide enterprise class infrastructure that enable you to scale your deployment as your users grow.
Integration with your existing data warehouse and OLAP cubes
While some vendors tout in-memory as a way of avoiding building a data warehouse, this option usually applies to smaller organizations that may only have a single source system. For larger companies that have multiple source systems, the data warehouse continues to be the ideal place to transform, model and cleanse the data for analysis.
Look for tools that are designed to integrate with and leverage existing BI environments. An in-memory solution that is tightly integrated into the visualization tool is critical. However, it is equally important that the visualization tool can also access your OLAP cubes and data warehouse tables without the need for an in-memory middle-layer. Without this option a purely stand-alone in-memory solution can lead to yet another version of the truth, adding complexity to your BI environment.
Yellowfin takes a flexible approach whereby the system administrator can configure the server to perform processing either against the in-memory database, or alternatively, push processing down to the underlying data store. The decision on which approach is optimal for a given deployment will depend a lot on the query performance characteristics of the data store. For example, a traditional OLTP data store may benefit significantly from in-memory processing, whereas a query optimized analytic data store may provide performance similar to or better than in-memory processing. Combining this flexible architecture with the cost advantages of not using an OLAP server gives customers choice and a BI platform that can grow as their data and analysis requirements do.
Ensure real time data refresh
Because reporting data is potentially extracted from a source system or a data warehouse and then loaded into memory, data latency can be a concern. Front-line workers in a customer service center, for example, need near-real-time, highly granular (detailed) data. If an in-memory tool contains last week’s product inventory data, it’s probably not of use to customer service reps. Thus, the suitability of an in-memory tool and the success of the deployment may hinge on the degree to which the solution can automate scheduled incremental data loads. One of the criticisms’ of some in-memory analysis tools is their lack of incremental load. This means that whenever a data refresh is required the entire data set need to be refreshed rather than just changed or new transactions. This increases the load times and means that refreshes cannot be frequent enough to enable near-real time reporting. This is nor the case with Yellowfin’s in-memory technology.
Minimize Administration overhead
In-memory analytic tools often introduce some of the same concerns that OLAP stores create: namely, they usually create another data source, with its own calculations and business definitions. This is where tools such as Yellowfin differ from other in-memory approaches: existing queries, reports and dashboards automatically take advantage of an in-memory database, seamless to users. Administrators are not adding calculations and business logic within another layer; they reside within the existing meta-data layer for reporting that is already built.
Web-based development and deployment.
Some in-memory tools are not nearly as Web enabled as their conventional BI counterparts. This seems to reflect both technology immaturity and a tendency to be a niche deployment. However, for successful adoption with minimal administrative overhead web based development and deployment is critical. Both the visualization tool and in-memory database need to be server based deployments to ensure data access security and application upgrades can be easily managed. Solutions such as Yellowfin, provide a single web based platform for delivering your Business Intelligence needs. From connection through to design, modeling and visualization, your users work within a fully integrated browser application that encourages collaboration and an iterative approach to report development - leading to analytical applications that meet the needs of your end users.
Data security must be of paramount concern
In Memory applications have the potential to expose significantly more data to end-users then ever before. This raises security issues regarding how data is accessed, where it is stored and who has access to that data.
In determining the best strategy for your in-memory deployment security needs to be foremost in your selection criteria. There are two aspects of security the location of your data. Where is it stored and is that storage secure? And secondly who has access to that data store. In terms of storage – the most secure location for your data is on a centralized server, whether hosted or internal. Not only is this more secure but it maintains basic controls regarding data governance.
To understand this consider a scenario where users are able to conduct complex queries by downloading up to 100 million rows of data to their desktop from many data sources, or data feeds from the Web. Sure the information can then be sliced and diced into reports or users can create BI applications on their desktops and share them with colleagues. Sounds great in theory but fraught with danger in practice. With this level of data on a laptop it is free to leave your premises and get lost or stolen in the worst case or published without any form of governance at best.
In addition to centralized storage your in-memory analysis need to conform to data security measures as well. These means that data access profiles for your users need to be adhered to through out your reporting process. Organizations spend an enormous amount of effort in securing their transactional applications and so it is critical that when it comes to the data they contain the same level of security is present. This means that users only have access to the data they are authorized to access, and that this access is changes as the employees role changes.
In summary when choosing an in-memory analysis tool set you do need to consider how it will reside within your enterprise architecture. Interaction with your current business intelligence environment, the security framework and the ability to deliver real time reporting are all critical aspects that need to be considered in your selection process.
Yellowfin Business Intelligence
www.yellowfinbi.com
Posted by Justin Hewitt at 5:15 AM | Comments (0)
May 4, 2010
Yellowfin Launches 5.0
Yellowfin is set to redefine what BI users and IT Departments will expect from Business Intelligence vendors
Leading Business Intelligence software provider, Yellowfin, today announced it would be launching its milestone release on May 5th, 2010.
Yellowfin 5.0 is set to redefine what BI users and IT Departments will expect from BI vendors. With faster deployment and faster analytics, Yellowfin 5.0 is set to establish new BI standards, all the extra functionality is integrated and three simple steps are all it takes for users to connect map and visualize their data.
Glen Rabie, CEO of Yellowfin says, “This is a quantum leap in BI performance. With Yellowfin 5.0 there is no need for the complex and expensive processes of developing ETL scripts and data warehouses. It really is a simple process that our beta customers have been delighted by. Yellowfin enables users to see and know their business in new ways and interactively explore data without limits”.
“Yellowfin 5.0 was the result of understanding how our customers wanted to work within the BI environment. The typical scenario was that deployment got bogged down due to query performance and the need to build data marts or data warehouses that would address these performance issues. As a result, business users had to wait for this tedious non-value added step to be completed before they could even write a single report, leading to frustration. So Yellowfin developed an in-memory database to address this need,” says Rabie.
Successful BI projects are measured by two core criteria: the speed of delivery and the speed of analysis. Traditionally there was a trade-off between the two. To achieve the analysis speeds required - complex project steps are required. However,
Yellowfin 5.0 has two major features that deliver a significant speed enhancement over traditional BI tools. These are:
1. An embedded in-memory database
2. A fully integrated user interface for all development steps
“What this means is that with Yellowfin users can rapidly develop and publish reports and dashboards since the number and complexity of the steps required for delivering a reporting project is significantly reduced (minimizing project costs and risks) without the need to compromise on the speed and efficiency of the reporting and analysis. And that thrills the business user,” says Rabie
Fast analysis, better insight and rapid deployment with minimal IT involvement —these are the leading benefits of in-memory analytics. With Yellowfin 5.0, In-memory analytics delivers decision insight with the agility that businesses demand. It’s a win for business users, who gain self-service analysis capabilities, and for IT departments, which can spend far less time on query analysis, cube building, aggregate table design, and other time- consuming performance-tuning tasks.
Ends
Download publications
In-Memory Brochure
http://yellowfin.com.au/Document.i4?DocumentId=104877
In-Memory Whitepaper
http://yellowfin.com.au/Document.i4?DocumentId=104879
eSite Case Study
http://www.yellowfin.com.au/Document.i4?DocumentId=10352
Location Intelligence Whitepaper
http://yellowfin.bi/Document.i4?DocumentId=102780
Demo Video - Dashboard
http://www.youtube.com/watch?v=DSDvmD3xeUg&feature=channel
About Yellowfin
Yellowfin is passionate about making Business Intelligence easy. Recently recognized among 25 rising companies that CIOs must know about, Yellowfin is a leading web-based BI solution that can be easily integrated into any third-party application or delivered as a stand-alone enterprise platform. Yellowfin is an innovative, fast and flexible solution for reporting and analytics, providing a full range of data access, presentation and information delivery capabilities. www.yellowfin.bi
For further information / interviews please contact:
Catriona McGauchie
Marketing & Communications Manager, Yellowfin
Direct line: 61 3 9090 0454 Mobile: 61 (0)428 368 371 Email: catriona.mcgauchie@yellowfin.bi
Posted by Justin Hewitt at 6:30 AM | Comments (0)
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