e-guide: improving business intelligence performance

E-Guide

Improving Business Intelligence

Performance

More and more organizations are implementing business intelligence

(BI) systems, including many small and medium-sized businesses

(SMBs) that previously considered BI tools to be out of their reach. As

these companies make their forays into the world of BI, often with SQL

Server as the underlying database, one of the most common concerns

they have is about system performance.

This SearchSQLServer.com E-Guide offers expert insight about what

organizations can do to improve the performance of their BI system

and new ways to improve BI performance and scalability. This E-Guide

addresses how to meet BI performance challenges:

• SQL Server business intelligence performance baked in for most

SMBs

• Deployment options increase for meeting BI performance

challenges

• SQL Server BI in the Cloud

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http://content.dell.com/us/en/enterprise/d/solutions/intel-and-dell.aspx

SearchSQLServer.com E-Guide

Improving Business Intelligence Performance

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E-Guide

Improving Business Intelligence

Performance

Table of Contents

SQL Server business intelligence performance baked in for most SMBs

Deployment options increase for meeting BI performance challenges

SQL Server BI in the cloud: feasible or fantasy?

Resources from Dell, Inc. and Intel



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SQL Server business intelligence performance baked in for most SMBs

By Don Jones

More and more organizations are implementing business intelligence (BI) systems, including

many small and medium-sized businesses (SMBs) that previously considered BI tools to be

out of their reach. As these companies make their forays into the world of BI, often with

SQL Server as the underlying database, one of the most common concerns they have is

about system performance -- and with good reason.

Large enterprises often can devote millions of dollars in IT resources to their BI systems:

powerful software, mega-sized servers, massive amounts of disk storage, dedicated teams

of technical workers, and so on. Those things can significantly improve the performance of a

BI system – but they’re definitely not in scope for most SMBs. So, what can smaller

organizations do?

BI systems are designed to provide answers to business questions, typically by

consolidating disparate information from systems across a company and letting end users

run queries or reports against the data. For example, you might be able to take a discrete

fact -- perhaps customer satisfaction metrics are falling -- and trace the reason for that

back to its source. Let’s say your company has been heavily marketing a particular product

and its sales are increasing, but the product is easily damaged in shipping and customers

are obviously unhappy -- and your shipping insurance claims are going up. It’s the ability to

consolidate all of that information into a single tool set that makes BI so powerful.

There are, broadly speaking, two ways of working with a BI system. The most traditional

way is via a data warehouse. Structured specifically to respond quickly to queries that

involve a number of different criteria, most data warehouses are updated at pre-set times,

meaning they don’t act against live data but instead operate with snapshots of information

from specific points in time. The performance of these systems is primarily derived from the

underlying database design and from the processes that load data into the data warehouse

from various organizational sources.



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The in-memory approach to SQL Server business intelligence

A somewhat newer technique is in-memory analytics. It can also be used to pull data from

multiple sources, but the BI connections between disparate data can be made in real time,

and the information is stored in the memory of an analysis server. In addition, in-memory

systems can support hybrid approaches that combine real-time data with historical

information from a data warehouse.

Microsoft Corp.’s PowerPivot for Excel software, which operates in conjunction with SQL

Server, is one example of a tool with in-memory analysis capabilities. In-memory analytics

performance is mostly a function of how powerful the analysis server itself is: The more

memory and the more (and faster) processors that a server has, the faster it should be able

to process queries.

To improve the performance of an existing BI system, you really have only two options:

• Design a more efficient system, or

• Run it on faster and more powerful hardware

The first option isn’t something that most SMBs are likely to have under their control. Often,

SMBs with limited internal IT resources purchase pre-built BI systems that combine a data

warehouse and BI software in what is effectively a black-box server. Or else they deploy

systems that were designed and built for them by a consultant.

The second element is easier to manage: Buy a bigger server. Or, for larger and more

complex BI systems, split the workload across multiple servers. But scaling out in that way

is complex and often requires a certain amount of redesign work to take advantage of

database techniques such as data federation and data partitioning -- which may put it

beyond the budgets and IT capabilities of many SMBs.

System design may dictate SQL Server business intelligence performance

Of course, scaling up a single server also costs money. The bottom line is that unless you’re

able to invest in new or upgraded hardware, the upper limits of your BI performance are



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often determined in advance by the design of the packaged BI system you choose, including

how well it makes use of SQL Server or whatever other database platform it’s built upon.

As a result, if you’re the buyer or architect of a BI system for an SMB, performance should

be your top concern after the data analysis features your organization needs in order to

meet its business goals. Make performance a real focus of your technology evaluation

efforts: Ask to see demonstrations of packaged systems running workloads with a data set

that’s representative of the amount of information you anticipate having in your BI system.

You also can grill the vendors about their system designs. The process, though, is like

buying a car: It's interesting to ask about the kind of engine that a vehicle has -- but

ultimately, you need to take it on a test drive because there's more than just the engine at

play. With BI systems as well, there are a lot of complex, interconnected components, and

the only way to check their combined performance is to try them.

ABOUT THE AUTHOR

Don Jones is a senior partner and principal technologist for strategic IT consulting firm

Concentrated Technology LLC.



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Deployment options increase for meeting BI performance challenges

By Don Jones

As an increasing number of companies look to implement business intelligence (BI)

systems, new ways of meeting their BI performance and scalability needs are emerging, in

the process giving potential technology buyers additional deployment options to evaluate

and consider.

At a basic level, most organizations -- especially those less-than-gigantic companies often

classified as small and medium-sized businesses (SMBs) -- have three very simple goals for

their BI systems:

• They have to provide reliable answers to business questions, meeting the overall

promise of BI itself.

• They have to perform queries quickly while also enabling users to interactively drill

through data sets as much as possible.

• They have to be easy to deploy, without years-long planning, design and

implementation cycles.

More specific capabilities differ from company to company. Everyone wants dashboards and

reports, but what people want to see in them varies. Those kinds of features are the major

points on which BI system vendors compete. But how can you ensure that the underlying

performance and deployment issues are addressed as part of a BI project?

One way is to focus on the combination of BI systems and database engines. Microsoft SQL

Server, for example, includes an Analysis Services component that is specifically designed

to handle BI workloads, and it’s entirely possible to build both custom and packaged BI

systems on top of that platform.



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Better system design begets better BI performance

There are some advantages to such approaches. The platform vendor (Microsoft, in this

example) often builds up significant experience in BI system design over time through all of

its dealings with customers and BI vendors. That shared experience can lead to better

system designs, and better-designed BI systems are better-performing BI systems.

Microsoft, to continue using it as an example, has a wealth of publicly accessible best-

practices information and system design patterns, along with in-the-trenches studies on

how to wring the best performance from BI systems built on SQL Server Analysis Services.

Another potential option is a Software as a Service (SaaS) approach to BI. Just as

companies are moving email, customer relationship management (CRM) and other IT

functionality into the cloud, you can purchase cloud-based BI technology from a growing list

of vendors.

SaaS BI systems offer the promise of rapid deployments along with access to a back-end

architecture that most SMBs couldn’t afford to build out on their own. That creates the

potential for Fortune 50-class performance -- but the cost of the SaaS BI architecture is

divided across numerous customers, making the capital and operational investment more

affordable for individual organizations.

Internal hurdles for SMBs on BI performance, functionality

As mentioned above, system design is the prime driver of business intelligence

performance. However, few SMBs can afford to employ a full-time BI design expert. That

means homegrown BI systems are often built for them by consultants, who may or may not

fully understand what a company needs from its BI system. They also may or may not be

around later to tweak the design to accommodate ongoing changes in the business

environment or correct initial design errors or misconceptions.

Packaged BI systems seek to avoid that problem by creating preconfigured product offerings

that are designed around common business concepts and practices, instead of requiring a

customized system for each customer. At a certain level, this out-of-the-box approach can



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work well. After all, most companies use packaged software for email, accounting, human

resources, enterprise resource planning, CRM and other functions. Because BI systems draw

much of their data from those kinds of operational systems, it stands to reason that -- for

certain companies -- packaged BI tools will meet business needs.

Such systems may be designed and tweaked by BI vendors or systems integrators for

optimal performance on SQL Server or another chosen database platform. Although the

black-box nature of preconfigured systems makes it hard for users to modify them for

increased BI performance, they often are easier and less expensive to implement than built-

from-scratch systems are, helping to address the deployment concerns that many SMBs

have about BI technology.

The good news is that with the rapid growth of BI as a product category, businesses now

have more choices than ever for obtaining or building a high-performance BI system.

Solutions to the BI performance challenge are out there -- you just need to find the right

one for your organization.

ABOUT THE AUTHOR

Don Jones is a senior partner and principal technologist for strategic IT consulting firm

Concentrated Technology LLC.



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SQL Server BI in the cloud: feasible or fantasy? By Don Jones

As surely as business intelligence (BI) and cloud computing have become marketing

buzzwords, the two IT trends have indeed come together. An increasing number of vendors

are offering cloud-based business intelligence systems, including SQL Server BI in the cloud,

often targeting them squarely at small and medium-sized businesses (SMBs).

Whatever you think of “the cloud,” BI in the cloud is something you have to pay attention to

if you’re considering implementing a BI system. Essentially, you’re looking at a Software as

a Service (SaaS) technology not unlike SalesForce.com, which is arguably the poster child

for cloud services. The advantages of a BI system in the cloud are numerous:

• You don’t install or implement anything (well, almost -- keep reading) in your own

data center. You just “turn on” the service one day and you’re up and running. Sort

of.

• You don’t need to worry about outfitting the right kind of server with tons of

memory, storage and processors -- the service provider handles it.

• You don’t need to know a thing about building a BI system, because it’s already

built. You’re buying a more-or-less “prepackaged” solution, in much the same way

that you probably bought your accounting and customer relationship management

(CRM) software.

• You will often be looking at a smaller -- possibly zero -- capital investment. Instead,

you simply pay monthly or annual service fees based on your usage of the SQL

Server BI system in the cloud.

That last bit is where you need to be careful: How is usage metered, and what will you pay

for it? Some providers charge based on the number of users who will be utilizing the BI

system; others charge based on how much data you’re storing, while still others use some

combination of these and possibly other factors. The cost factor is always the big warning

point in a SaaS system, because it isn’t always as straightforward as the host-it-yourself

solutions we’re all used to.



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Another point of caution -- or at least an area you need to learn -- concerns the fact that BI

systems, by definition, need to integrate pretty tightly with your data center, something

SaaS solutions haven’t typically needed to do.

A cloud-based CRM system, for example, may not need to integrate with any of your other

back-end systems (although more of them are gaining the ability to do so). A BI system, by

contrast, is useless if it can’t access a wide range of your existing corporate data.

Today, cloud BI providers often achieve this integration by requiring some infrastructure to

be deployed in your data center -- often in the form of agents that collect data from your

existing systems.

Some BI providers are capable of collecting data from cloud-based storage, such as

Windows Azure or Amazon’s EC2/S3 infrastructure, but not many companies are storing

their back-end data (things like sales figures and financials) in the cloud -- at least not yet.

Some providers require you to do a traditional extract, transform and load (ETL) cycle to

upload your data to their servers for analysis; others enable your live data to be connected

to the BI system through agents, connectors and other software components.

How your data gets to the cloud is the big question, and it’s the main area where today’s

cloud BI vendors differentiate themselves. Make sure you focus on that area when

evaluating systems, along with the more obvious user functionality like dashboards, reports,

scorecards and the like.

ABOUT THE AUTHOR

Don Jones is a co-founder of Concentrated Technology LLC, the author of more than 30

books on IT and a speaker at technical conferences worldwide. He can be reached through

his website at www.ConcentratedTech.com.



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Resources from Dell, Inc. and Intel

Improving Data Center Performance through Virtualization of SQL Server

Databases

SQL Server 2008 Upgrade Series: Business Strategies

SQL Server 2008 Upgrade Series: Performance

About Dell, Inc. and Intel

Dell and Intel are strategic partners in delivering innovative hardware solutions to solve

your most challenging IT problems. Together we are delivering virtualization optimized

solutions to maximize the benefits of any virtualization project.

http://www.bitpipe.com/resource/1287069673_573




http://content.dell.com/us/en/enterprise/d/solutions/intel-and-dell.aspx