This article explains what SQL Server Integration Services configurations are used for, why you should use Integration Services configurations, and what options you have for leveraging configurations. It will also make some simple recommendations that are based on my experiences of building Integration Services packages in a real-world environment. An understanding of the terms “package”, “Business Intelligence Development Studio”, and “dtexec.exe” in the context of Integration Services is assumed.

There five basic types of Integration Services configurations.

• XML Configuration File
• Environment Variable Configuration
• Parent Package Configuration
• Registry Configuration
• SQL Server Configuration

Read Best Practices for Integration Services Configurations

Reference: Pinal Dave (http://blog.sqlauthority.com)

As PASS is now one week away and I am all excited for the same. I am going to attend following two sessions for sure. I encourage all of you to also visit the same sessions. We can all talk about SQL , SQL Integration as well Beyond Relations.

First sessions I will be attending of Rushabh Mehta, he is Managing Director of Solid Quality India.

Overcoming SSIS Deployment and Configuration Challenges

Presenter:
Rushabh Mehta (Solid Quality Learning)

Session Details

It is no secret that a main deficiency of SSIS is deployment. Have you wanted to punch a wall before when trying to move a package from one server to another? You’re not alone. This session will be more than just SSIS deployment anger management. We’ll look at how to overcome the deployment challenges by considering configurations, package and connection security, and deployment approaches. And don’t miss the decision workflows that will help you down the right path on choosing the right storage and deployment approaches depending on your situation!

Second sessions I am going to attend of Jacob Sebastian, he is founder of BeyoundRelational.com.

SQL Server 2008 – Create powerful XML Schema collections to validate your XML documents

Presenter:
Jacob Sebastian (beyondrelational.com)

Session Details

XML is getting more widely used both inside and outside SQL Server. Stored procedures and functions that accept XML parameters or generate XML documents are part of almost every database project these days. When information is exchanged in XML format, there needs to be an agreement between the sender and receiver about the structure and content of the XML document. Using an XSD (XML Schema Definition) Schema, you can validate the structure and content of an XML document. SQL Server introduced XML Schema Collections in SQL Server 2005 and added a number of enhancements in SQL Server 2008. An XML data type variable or column that is bound to an XML Schema collection is called TYPED XML. When a TYPED XML column or variable is modified, SQL Server will validate perform the validations defined in the SCHEMA Collection and the operation will succeed only if the validation succeeds. In this session we will discuss SQL Server XML Schema collections and see how to create powerful XML Schema Collections to validate XML documents with diverse structure and content.

I am also preparing my schedule as I want to attend almost all the sessions as I can. Please read following related post about SQL PASS.

Related Articles:
Why I am Going to Attend PASS Summit Unite 2009- Seattle

Reference: Pinal Dave (http://blog.sqlauthority.com)

What is Business Intelligence

Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data from various data sources, thus providing enterprise users with reliable and timely information and analysis for improved decision making. To put it simply, BI is an umbrella term that refers to an assortment of software applications for analyzing an organization’s raw data for intelligent decision making for business success. BI as a discipline includes a number of related activities, including decision support, data mining, online analytical processing (OLAP), querying and reporting, statistical analysis and forecasting.

Business Intelligence for Success

Business intelligence equips enterprises to gain business advantage from data. Once an organization is powered with BI it can anticipate enhanced turnaround time on data collection, come up with fresh ideas for novel business initiatives, foresee accurate picture of customer needs and demands, and perform more targeted marketing campaigns. In addition, it will gain enhanced knowledge that will help it advance its brand into the top slot in terms of market share, cut down its client churn, reduce its overheads and also diminish delays in supply chain, among other advantages. Decisions purely based on the gut feeling cannot assure success; but in BI’s fact-based decision-making framework, confident decisions can be made for assured business success. Further, BI makes an organization agile thereby giving it a competitive edge in today’s evolving market condition.

Business Intelligence Scenario

Every day, a dairy company collects from 2,000 stores information which is uploaded to servers at its headquarters at the end of the day. This information is used by the chain’s main office to instantly analyze key operational measures such as the number of dairy products sold, profits, trends, and so forth.

Next day, by early morning the company’s managers receive performance data. Next, they verify current revenue, time required to perform each job, and other performance measures. With BI, franchisees with multiple locations can have consolidated views, as can the company’s regional managers.

This scenario clearly explains how implementation of Business intelligence can be very fruitful for an organization. BI can catalyze a business’s success in terms of

Revenues

• Distinguish the products and services that drive revenues.
• Rank customers and locations based on profitability.

Customer relationship management

• Categorize low-value customers and work toward improving their value.
• Find customer relationship issues early and take timely action to resolve them.

Sales and marketing

• Aim at high-value customers to minimize marketing risk.
• Rank the success of product promotions based on product and market segment.
• Find what is in the sales pipeline

Business Intelligence Terms

Ad Hoc Query – Ability to create an immediate ‘request for information’ using an analytical reporting tool to answer a specific business-related query.

Aggregation – Predefined summaries based on comprehensive data in the data warehouse.

Atomic data – Topmost level of detail in the data warehouse.

Attribute – Field represented by a column in reports, tables and charts.

Cube – A powerful analysis tool that is used for viewing and analyzing data in a multi-dimensional format, from any angle, in any combination, through a ‘slice and dice’ and drilldown approach.

Data – Factual information for analysis.

Data Mart – A logical subset of related information, typically around one or a few business processes, or a particular subject area.

Data Warehouse – A repository of well-organized corporate data for Business Analysis and Reporting. It is also a collection of data marts.

Database – A collection of data arranged for convenient and quick search and retrieval.

OLAP – Online Analytical Processing is a category of database software that provides an interface to help users quickly and interactively scrutinize the results in a variety of dimensions of the data.

Balanced Scorecard – A Performance management tool that recapitulates an organization’s performance from several standpoints on a single page.

Dashboard – A reporting tool that presents key indicators on a single screen, which includes measurements, metrics, and scorecards.

Data Cube – A multidimensional structure (typically over three dimensions) that forms the basis for analysis applications, allowing various types of calculations and aggregations.

Data Mapping – Process of spotting a source data element for all data elements in the target data warehouse environment.

Data Quality – It is related to facets such as accessibility, comprehensiveness, exactness, steadiness, significance and timeliness of data.

Data staging – A system where operations like data extraction, transformation and loading operations are executed.

Dimension Table – It contains attributes that describe fact records in the fact table. For instance, pupil enrollment is a central fact table with several dimensions linked to it such as Faculty, Term, and Degree.

Drill Down – A feature that allows users to click on an item to navigate through hierarchy and move to a level of better detail.

EIS – Enterprise Information System – A category of applications and technologies for presenting and analyzing corporate and external data for various management purposes.

ETL – Extract, Transform and Load -It is a three-step process at the center of data warehousing. In the first step, operational data is extracted from multiple sources. In the next step, it is transformed into the required type. In the final step, data is loaded into the data warehouse.

Forecasting – It is the formulation of trends, predictive models, and scenarios to prepare for the future for improved decision making.

Gap analysis – Study of whether the available business data supports business requirements, thus answering questions related to data accessibility, amount of data, missing data, and legacy systems. It examines information and decides on the resources and efforts required to satisfy requirements.

Granularity – Level of detail or summarization of data in the data warehouse. The more the detail, the higher the level of granularity.

Institutional performance management – The process of basing an organization’s actions and decisions on actual measured results of performance. It incorporates performance measures, benchmarks, and goals to attain best results.

Measures – A quantifiable, specific piece of information.

Metrics – Measures of performance that observe progress and evaluate trends within an organization.

Normalization – Standard database design technique for relational databases.

Slice and Dice – Multidimensional tools allow users to view data from any angle. The ability to select various angles to view data from is called slice and dice capability.

Snapshot – View of data at a particular moment.

Reference: Pinal Dave (http://blog.SQLAuthority.com), DNS

I have wonderful experience at my recent Business Intelligence tour. I will write down in detail about my experience at different location. However, today I would like to talk about one particular question which was asked at all the locations. It was about SQL Server Accelerator for Business Intelligence (BI). Many attendee asked me how to use this tool.

SQL Server Accelerator for Business Intelligence (BI) is no more supported by Microsoft. Microsoft does not provide any support for this solution accelerator and has no plans to release future versions. Microsoft SQL Server 2005 and later versions include most of the functionality of the accelerator and are supported according to the Microsoft Product Lifecycle.

For the same reason, this tool is not included in the course as well new developer should not focus learning the same.

Reference : Pinal Dave (http://blog.sqlauthority.com)

In my recent Business Intelligence Training Roadshow August September 2009 I quite often get request to provide more details about Analysis Service Cubes for Excel 2007 PivotTable. Here is the white paper on the same subject.

According to MacLennan et al. (2009), data mining is defined as “the process of analyzing data to find hidden patterns using automatic methodologies.” Consider the following simple example that explains this concept. By analyzing the data on the items purchased from a supermarket or a chain of such stores, information on the products that are sold most can be obtained and accordingly supply of that particular products are increased and vice versa. Data mining, in short, is an analytical activity that studies the hidden patterns in a huge pile of data after appropriately classifying and sorting it.

Who all are involved in Data Mining?

Data mining is an activity, which can be programmed, that involves the analysis of data and finally revealing the hidden patterns. Architects, Developers and Analysts are involved in the data mining process.

Data mining is usually carried out by an Analyst. However, it is not necessary that every time, he/she will be able to identify all the hidden patterns of a particular data set, irrespective of its size. Finally these identified patterns are converted into useful information for business purpose. A Developer combines data mining with application solutions, and an Architect understands the needs of the developer and the analyst and meets them accordingly.

Microsoft and Data Mining

Microsoft provides a wide range of data mining options, which includes collaborative solutions and ad hoc analysis (in MS Office Excel). A free plug-in is available in MS Office Excel 2007, which helps the analyst to analyze the data patterns. In addition to this plug-in, the Business Intelligence Development Studio (BIDS) that is free with the SQL Server can also be used for data mining purpose.

It should be noted that data mining is not done on the basis of any known data patterns or any other additional information. The results obtained of data mining are generated from the data presented and not from any other resources. Microsoft data mining applies mathematical techniques on the available data set to obtain models. In addition to BDIS, the .NET framework and Data Mining extensions (DMX) language is also provided by Microsoft for custom solutions. At times, data mining is also known as machine learning.

Results of Data Mining – Data Mining Models

Microsoft data mining results in data mining models, which are statistical information – either predictive or descriptive. A Microsoft Mining Model consists of the following three components: metadata, which is information about the data; patterns, which are mathematical formulas or rules; and bindings, where the data is defined. The statistical results may not be understandable in relation to a business perspective. Hence, these results or models must be translated to useful business information. One who engages in data mining is responsible for creating a link or relation between the resultant data model and the respective business problem.

Role of Data Miner (or Analyst)

A data miner should undergo adequate training with regard to all the tools and technologies used in mining and should not limit himself/herself to only those tools that are required for that particular organization/business. In fact, it is the responsibility of the organization to provide training to the data mining professional on a broader perspective. Data mining is never complete without the analyst. The application of the results of data mining to a specific business significantly depends on how far the analyst has understood the industry-specific objectives.

Applications of Data Mining

Data mining is used in various applications such as forecasting business and customer trends, detecting fraud (especially in the banking sector), generating customized advertisements, grouping customers on the basis of their purchasing trends, and risk analysis.

Benefits of Microsoft Data Mining

Microsoft data mining is extensible. It can be licensed through SQL Server 2008 (or SQL Server 2005) and it is compatible with other technologies, thereby allowing access to data in different formats. Microsoft data mining can also be used for business intelligence solutions and it is scalable unlike other data mining products.

Reference : Pinal Dave (http://blog.sqlauthority.com)

SQL Server 2008 R2 introduces new management tools to help improve IT efficiency and productivity. Investments in application and multi-server management will help organizations proactively manage database environments efficiently at scale through centralized visibility into resource utilization. Such investments can help streamline consolidation and upgrade initiatives across the application lifecycle—all with tools that make it fast and easy.

This paper introduces the new extensions in SQL Server Management Studio and the Control Point Explorer, and it walks through the simple process of setting up a SQL Server managed server group, including SQL Server Control Point installation, enrolling an instance into central management, extracting Data-tier Applications from existing deployments, and deploying Data-tier Applications to the new managed server group.

Read whitepaper Application and Multi-Server Management

Reference : Pinal Dave (http://blog.sqlauthority.com)

Posted in Business Intelligence, Data Warehousing, SQL, SQL Add-On, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQL White Papers, SQLAuthority News, T SQL, Technology ]]> http://blog.sqlauthority.com/2009/08/30/sqlauthority-news-application-and-multi-server-management/feed/ 0 pinaldave http://blog.sqlauthority.com/2009/08/25/sqlauthority-news-business-intelligence-training-roadshow-august-september-2009/ http://blog.sqlauthority.com/2009/08/25/sqlauthority-news-business-intelligence-training-roadshow-august-september-2009/#comments Tue, 25 Aug 2009 01:30:54 +0000 pinaldave http://blog.sqlauthority.com/?p=6653 ]]>

UPDATE : This is FREE training.

I quite often receive request from readers and expert from all over the world if I do any training for SQL Server. Currently I am on Tour of 8 different stats of India and will be training on Business Intelligence Boot Camp.

Here is quick image of the topics, which I am going to cover this boot camp.

Currently, I am schedule to deliver the same course in many of the cities as described below.

Let me know if you are interested in doing similar session at your city or organization and we can arrange one based on my upcoming schedule.

Reference : Pinal Dave (http://blog.sqlauthority.com)

Today, we have a very basic thing to go over. Few days back, I was discussing with one of my friends regarding BI. He told me that he knows that BI stands for Business Intelligence but he would like to know what languages BI uses to achieve the goal. The reason I found this question very interesting was because     I was asked the same question two weeks back at TechEd on Road Ahmedabad. I had promised one of the attendees that I will reply to his question soon. This question, which my friend asked recently, reminded me of the same. Let us go over the languages of BI very quickly. Again, these are just definitions and there is much more to learn. Moreover, to master each language it may take years.

MDX – Multidimensional Expressions. This language is used for retrieving data from SSAS cubes. It looks very similar to T-SQL, but it is very different in the areas of conceptualization and implementations.

DMX – Data Mining Extensions. This is again used for SSAS but rather than cubes it is used for data mining structures. This language is more complicated than MDX. Microsoft has provided lots of wizards in its BI tools, which further reduced experts for learning this language which deals with data mining structures.

XMLA – XML for Analysis. This is mainly used for SSAS administrative tasks. It is quite commonly used in administration tasks such as backup or restore database, copy and move database or learning meta data information. Again, MS BI tools provide lots of wizards for the same.

After writing the above definitions, I feel my information is incomplete as these are just very basic information and do not provide much value. I will cover interesting aspects of these languages in near future. In SQL Server Management Studio, you can write the queries in the desired languages using top menu bar.

Reference : Pinal Dave (http://blog.SQLAuthority.com)

What is Business Intelligence

Business intelligence (BI) is a broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data from various data sources, thus providing enterprise users with reliable and timely information and analysis for improved decision making. To put it simply, BI is an umbrella term that refers to an assortment of software applications for analyzing an organization’s raw data for intelligent decision making for business success. BI as a discipline includes a number of related activities, including decision support, data mining, online analytical processing (OLAP), querying and reporting, statistical analysis and forecasting.

1 What is Business Intelligence
2 Business Intelligence for Success
3 Business Intelligence Scenario
3.1 Revenues
3.2 Customer relationship management
3.3 Sales and marketing
4 Business Intelligence Terms

Read complete article here.

Reference : Pinal Dave (http://blog.SQLAuthority.com)

I am very excited to share this news with all my readers. If you all remember I had already given a hint on my blog just two days back; I mentioned that we are going to host a grand event for Gandhinagar SQL Server User Group. In the past, Gandhinagar SQL Server User Group events have been more successful than we expected. Now, this event will grow even bigger as both Gandhinagar SQL Server User Group (President Pinal Dave – SQL MVP) and Ahmedabad SQL Server User Group (President Jacob Sebastian – SQL MVP) will come together for the event. This upcoming event will be known as SQL Server Energy Event.

This event is going to be one of the biggest events we have organized so far. A renowned international speaker Rushabh Mehta (SolidQ Mentor – SQL MVP) will be joining us for the event. Rushabh is a familiar name in SQL Server community and his expertise in the domain of Business Intelligence is commendable. I am a big fan of him and I have listened to many of his webcasts. In March 2009, I met Rushabh at Microsoft MVP Summit in Seattle. He promised me that he will surely participate in a session for SQL User Group. He has kept his promise and within 2 months of his promise he is here to do a SQL Session with us. This is one of the lifetime opportunities to see him in action in user group. Besides, this is the very first time he will be taking a session in SQL User Group in Gujarat, India. Further, for the very first time in Gujarat three SQL MVPs will be present at one event – Rushabh, Jacob and Pinal. This event is going to be a unique event in every aspect.

Organizing such a large event in a very short duration is very arduous and challenging, but I must thank the host of the meeting Digicorp for promptly arranging all the necessary logistics. This time, there will be take-aways for all the attendees. We will have a wide array of gifts including T-Shirts, Pen, Books, Hats, to name a few. Also, every attendee will surely get the famous SQL Server Cheat Sheet. This cheat sheet became so popular at TechEd that we ran out of them. Here is the opportunity to become a proud owner of a professionally printed cheat sheet, which you can get autographed by any of the available MVPs. What’s more, you can even get yourself photographed with Rushabh. This event will follow up with some light snacks as well. So many interesting things will happen at one event, I am sure you certainly don’t want to miss this opportunity. So make sure not to miss this exciting event!

I am expecting this event to be to be swarming with attendees. If you are interested in participating in this upcoming UG meeting you are requested to register at Gandhinagar SQL Server User Group or send me an email at pinal “at” sqlauthority.com. Registered attendees and those who have sent me email will be guaranteed a place in the meeting and they will also receive  the gifts.

Biodata of Speaker – Rushabh Mehta

Rushabh Mehta is a Mentor for Solid Quality Mentors’ global Business Intelligence division, based in USA, and is also the Managing Director for Solid Quality India Pvt. Ltd.

Rushabh has been actively working with Microsoft SQL Server platform since 1998 and has been designing and developing large-scale BI systems since 2001, including predictive-analysis systems, health-care solutions as well as a multi-terabyte financial decision support system. Rushabh was also instrumental in designing and building an analytical platform to support the Microsoft Windows Azure platform. His experience spans a wide breadth of industrial sectors including manufacturing, retail, finance and government working with clients such as Raymond James Financials, Jackson Hewitt, Publix, US Dept of Veterans Affairs, US Dept of Defense and Microsoft.

Through his experiences, Rushabh has also developed a number of industry best practices. He has also developed and delivered training courses on Business Intelligence practices and technologies and is also an active speaker at a number of large conferences like PASS and TechEd and also frequently speaks at SQL Server and Business Intelligence user groups around the world. Rushabh also serves as the Executive Vice President of Finance for the Professional Association for SQL Server (PASS), which is the largest global user-driven community for SQL Server Professionals with over 170 chapters world-wide and over 45,000 members.

Keynote Topic – Navigating through a turbulent economy with Microsoft Business Intelligence

There is no denying that the global economic situation is challenging. Is your company prepared to weather the storm? Microsoft business intelligence helps you access real-time information, find profitable customers & inefficiencies, and save money. This session features guidance on new ways to find value from your existing Microsoft business Intelligence investments. But it also includes a preview of what is to come in the future – new technologies for self-service analysis and self-service reporting that will change the way in which you think about BI.

The agenda of meeting is as follows:

May 20, 2009 – Wednesday

6:30 PM – 6:40 PM – Welcome and Introduction – Pinal Dave
6:40 PM – 8:00 PM – Navigating through a turbulent economy with Microsoft Business Intelligence – Rushabh Mehta
8:00 PM – 8:05 PM – Thank you note – Jacob Sebastian
8:05 PM – 8:15 PM – Gifts Give Away
8:15 PM – 8:30 PM – Light Snacks

The Best Participant of the event will get the chance to get photographed with all the three SQL MVPs.

Meeting Location:
Digicorp House,
Nr. Kashiram Agrawal Hall,
Ambawadi,
Ahmedabad-380015
Gujarat, India
Web – Digicorp

Reference : Pinal Dave (http://blog.SQLAuthority.com)

Originally posted : http://blog.sqlauthority.com/2009/05/19/sqlauthority-news-sql-server-energy-event-mark-your-calender-may-20-2009/

It is my pleasure to announce Gandhinagar SQL Server User Group Meeting on May 20, 2009 Wednesday. Mark this date as we will be having international speaker Rushabh Mehta of SolidQ attending our session. Rushabh Mehta is a Mentor for Solid Quality Mentors’ global Business Intelligence division, based in USA, and is also the Managing Director for Solid Quality India Pvt. Ltd.

I will have more information about his technical session, location and meeting time tomorrow.

This will be once in a life time opportunity. If you are in Gujarat state, India and you do not attend this session, you will for sure miss something.

Please register at http://gandhinagar.sqlpass.org/ and send me email at pinal “at” sqlauthority.com if you are planning to attend the session.

Reference : Pinal Dave (http://blog.SQLAuthority.com)

This article is submitted by Nupur Dave

Future of Business Intelligence and Databases

The term business intelligence (BI) was coined by Howard Dresner in the early 1990s. He defined Business Intelligence as “a set of concepts and methodologies to improve decision making in business through use of facts and fact-based systems.” In a time when data warehousing was considered leading-edge he created the vision that led to the development of business intelligence, as it is known today.  The once visionary BI is now commonplace and in near future a momentous transformation is about to take place.

BI is all set to bring information democracy where end users across an organization will be able to view information related to their segment. Further, with the rising consumer expectations there will be demand for capability requirements of BI as well.

Information Democracy with Business Intelligence

BI plays a crucial role in providing cost-effective, comprehensive insights into business processes that help organizations make informed, strategic decisions that assure enhanced business results. Not long ago, BI was the domain of statisticians and corporate analysts. Only the selected few could access BI. Today, BI is spreading to nearly every strata of organization, as companies attempt to provide critical data to business users who need it to perform their jobs. It is quite evident that BI is instrumental in bringing information democracy and it provides everyone the insights they require – delivering information to the right people at the right time across the enterprise. More and more organizations are expected to empower their employees with BI for productivity and operational gains.

Business Intelligence and Performance Management for competitive advantage

Today, when economic downturn is adversely affecting the world market, making insightful decisions about major changes in their business and markets has become crucial for organizations. They need to reconsider their strategies and operating plans. Only companies that can anticipate emerging trends and opportunities, refocus business strategy and vision, and align resources to maximize performance can effectively deal with the adversities of economic downturn and gain competitive advantage. BI and Performance Management brings business sensibility with enhanced visibility and insights, by delivering accurate and latest information to the right people for faster, improved, strategic and tactical decision making. Companies have increasingly starting realizing the importance of timely performance information to improve results, which will further make way for the rising demand for BI and Corporate Performance Management Solutions.

Business Intelligence via Software As A Service (SaaS)

It is being anticipated that in the coming years a number of organizations will have an industry-specific analytic application delivered via software as a service (SaaS) as a standard component of their BI portfolio. Information aggregators will bank on SaaS to deliver domain-specific analytic applications, which are made from industry data they assemble, and bring the balance of power in the BI platform market in their favor. Organizations will share their data with only those aggregators that can assure security as well as confidentiality. Thus, countless information aggregators offering SaaS analytic applications might appear; however, a virtual monopoly is expected to remain within each vertical niche owing to the high barricade that blocks the entry for others.

Business Intelligence and Social Software

Collaborative decision making will soon become the norm, which amalgamates social software with BI Platform capabilities. With social software users can tag assumptions made in the decision-making process to the BI framework, which significantly enhances the business value of BI as it ties all the good. Take for instance, in order to decide how much to invest in marketing a new product, users can tag their assumptions about the future sales of that product to a key performance indicator (KPI) that measures product sales. Whenever the KPI surpasses a threshold the BI platform would send alerts to the user to inform the decision makers about assumptions that no longer hold true.

With the advent of social software it has become easier to utilize the upsurge of interest in informal collaboration. As an alternative to the advancing of the usual top-down decision-making initiative, social software will be employed to collaborate and make decisions.

Business Intelligence Across All Sectors

BI is on its way to become an integral component of every type and size of organization across all sectors, including Real estate, IT, mobile devices, governmental agencies, scientific and engineering communities and R&D labs, banking and insurance, to name a few. BI can effectively deal with industry-specific constraints, operations and objectives thereby helping organizations better understand their customers, optimize their operations, minimize risk, manage revenue, and ultimately improve their results. More importantly, it is expected that in a couple of years BI will soon replace the gut-feel management with real data-based decision-making.

Business Intelligence For Real-Time Data

Today, consumers are demanding faster and improved services from businesses. As it has become imperative for companies to pay attention to consumer satisfaction in order to stay competitive they are depending even more on BI. They now demand near real-time analysis for intelligent decisions for business success. The rising demand for near-real-time data analysis is making way for a new framework for business intelligence. BI 2.0 is the recently-coined term to describe the acquisition, provision and analysis of real- time data, which was earlier lacking in BI. BI 2.0 is a part of the constantly developing business intelligence industry and indicates the next step for BI.

In near future, companies will switch from the traditional model of making business adjustments on a quarterly basis to business intelligence and performance management tools to make real-time shifts in strategy to respond to changes in the marketplace.

Over the coming years, business intelligence will undergo transformation that will have a broad and lasting impact. It will revolutionize the way that we think about business and the way business decisions are made. It’s only when thoughtful analysis supersedes gut feeling and conventional perception, we will enter the next level of business intelligence that will empower businesses with the capacity to reason, prepare, forecast, resolve issues and innovate.

Reference : Nupur Dave (http://blog.sqlauthority.com)

Business Intelligence
Business intelligence is a method of storing and presenting key enterprise data so that anyone in your company can quickly and easily ask questions of accurate and timely data. Effective BI allows end users to use data to understand why your business go the particular results that it did, to decide on courses of action based on past data, and to accurately forecast future results.

Data Warehouse
A single structure that usually, but not always, consists of one or more cubes.

Data Mart
A defined subset of a data warehouse, often a single cube from a group. It represents one business unit.

Cube
A storage structure used by classic data warehousing products in place of many. Cube usually present data that is aggregated, rather than each individual item. Cubes present a summarized, aggregated view of enterprise data, as opposed to normalized table sources that present detailed data.

Decision Support System
The term’s broad definition can mean anything from a read-only copy of an online transaction processing (OLTP) database to a group of OLAP cubes or even a mixture of both.

ETL
ETL is abbreviation of Extraction, Transform, and Load.

OLAP
OLAP is abbreviation of online analytical processing.

OLTP
OLTP is abbreviation of online transactional processing.

Reference : Pinal Dave (http://blog.SQLAuthority.com) , SQL SERVER – Data Warehousing Interview Questions and Answers Complete List Download