All classifieds - Veux-Veux-Pas, free classified ads Website.One moment, please

Looking for:

- Microsoft SQL Server Business Intelligence Development 

Click here to DOWNLOAD

   

 

Microsoft sql server 2014 business intelligence development beginners guide pdf free -

 

Our team of global e-learning experts has done in-depth research to come up with this compilation of Best Free Online Certifications, Courses, and Training for We are sure it will help you find what you are looking for. One of the widest ranges of courses and classes can be found online for free on LinkedIn Learning Lynda. You will get to learn the most in-demand tech, management, and creative skills from industry experts which will help you add value to your work while helping you grow in your career.

A lot of people know LinkedIn Learning as the erstwhile Lynda. So you can enroll in and complete any course of your choice at zero cost. You can Sign up Here.

What seems to still be a secret for many is the fact that almost all programs on global university training partner Coursera are now available for freefor a short windows not updating free that is.

This includes courses from Stanford University among a host of other famous universities and colleges globally. What matters here is the part that you can simply choose a training program you seem to have a liking for, and then enroll перейти на источник it at no cost, and evaluate the same by yourself. If after a few days you like it enough you can pay and continue further, otherwise, you can not pay and enjoy the free content while it lasts.

Sounds like a sweet deal to us! On Coursera, you will find free business certifications, free online training courses, free it certifications, and much more. You may also want to check out the list of the Best Coursera Certifications. If you dream about getting educated from one of the top universities then you should definitely check this series of programs. Learn from the experts and faculty who are always engaged in teaching and research to push the boundaries of human knowledge.

You can get rewarded with a free certificate, for completing any course, on any platform online. This can be across any subject category, any learning domain, and any duration. There are special certificates as you move up the ladder, the more you learn, the more you earn. Being certified in various Google courses can help you build a strong portfolio or start your own journey in multiple fields like Digital Marketing, Cloud Computing, Mobile App Development, etc.

To help you initiate your journey as a Google Certified individual, we have created this list of best Google certification courses that are offered by some of the well-known e-learning platforms like Microsoft sql server 2014 business intelligence development beginners guide pdf free, Google Digital Garage, Google Analytics Academyetc. Enrolling in these lessons will help you build a strong understanding of various digital marketing techniques, cloud storage, BigQuery, application Development, and much more.

Furthermore, after completing each course with the given assignment, you will receive a certificate of completion that can be shared with employers or LinkedIn profiles. Wow is the word! You can Sign up here. Udemy has got some of the best courses by some microsoft sql server 2014 business intelligence development beginners guide pdf free trainers all over the world. These are people who have been working in a certain domain for over decades, people who have taught at some of the biggest colleges globally and have taught thousands of students online.

The tutorials and courses created by them are highly rated, well-curated, and regularly updated. All that makes Udemy a favorite destination for students and professionals looking for affordable and free courses online.

On completion of a course, you get a certificate of completion. You may also be interested in checking out our compilation of Best Udemy Courses. To help people during the Corona Lockdown, Coursera has joined hands with leading global universities and launched Free Courses from leading colleges. Ever since being established inThe University of California has been committed to innovation in teaching and learning. UC Berkeley marks this commitment by facilitating online education initiatives including online degree programs, credit and non-credit courses, and MOOC projects.

Quality courses from UC Berkeley are now available for students to benefit from all over the world. Dive in to find an abundance of knowledge waiting for you on the other side. Udacity is a leader when it comes to online learning and it provides a tonne of resources to learn from for absolutely free. To earn the certification, enrolment in the programs require a certain price but if you are only interested in gaining access to the content and learning then Udacity can be very helpful in that aspect.

Go ahead and take the course that suits you, to supplement your knowledge or just delve into a completely new topic. With an impressive array of top colleges and universities such as MIT, Harvard, Berkeley on their panelthey microsoft sql server 2014 business intelligence development beginners guide pdf free one impressive place to hone your skills online. You will find some of the best business certifications, online certifications, free online it training, and much more.

You may also want to check out the Best edX Courses available online. If you want to gain critical knowledge of individual concepts within a field then these programs will help you with that.

The microsoft sql server 2014 business intelligence development beginners guide pdf free include an abundance of subjects such as languages, media studies, journalism, public relations, health and fitness, business studies, computer programming, networking, and much more! Use the search bar, career guide to find out the best choices for your chosen field.

We have compiled a list of some of the best free-to-use coding classes available online. This is one of the best options if you want to build strong fundamentals of coding. It includes courses from Codecademy, edX, Coursera, Datacamp, and many other course providers that specialize in this field.

The lessons do not microsoft sql server 2014 business intelligence development beginners guide pdf free focus отличный, sony vegas pro 9 free free все the theory and syntax but practical learning as well. So get started with writing working code from the very first lectures which will give you confidence in the techniques and methods covered in the videos. There could be a variety of reasons why you may be interested in learning Python.

Right from data science, machine learning, artificial intelligence to countless other applications, Python stands microsoft sql server 2014 business intelligence development beginners guide pdf free as a high-level general-purpose programming language.

To help you in your Python journey, we have put together a list of some of the best and freely available Python courses that can help you take your skill to the next level. You can learn from the top universities all over the world, leading instructors who teach online, or even pick up essential skills from engaging tutorials.

With over options, Udemy makes sure that you can learn the IT skill of your choice irrespective of your current experience level. The lessons are divided on the basis of difficulty level namely beginner, intermediate and advanced. Filter on the basis of topics, level of difficulty, process, language, features, and ratings to get programs better aligned to your requirements. The courses on this non-profit platform are primarily aimed to provide free world-class education to students.

Get guidance to gain a better understanding of your coursework, complete your homework and prepare for your advanced placement examinations. There are lectures on an array of subjects such as mathematics, science, computing, arts and humanities, economics and finance, test prep. These edX lectures are taught by Microsoft experts and are perfect for hands-on learners. Broaden your experience with cutting-edge technologies in areas like cloud services, mobile development, and data sciences.

The classes can be audited for free by anyone starting from students to seasoned technologists. With hundreds of IT training programs, this academy makes it easy to find the apt course to elevate your career. The classes are divided based on your current experience level namely developers, IT pros, and data pros. You can источник into database, web, cloud, game, or mobile development, virtualization, enterprise security, Azure, DevOps, business intelligence, advanced analytics, SQL server to name a few.

There are classes designed specifically for beginners as well to help them get a solid start before focusing on a particular specialization. One hidden gem not many know about is TedEd. Explore topics as well as interdisciplinary subjects such as chemistry, calculus, entrepreneurship, energy, transportation, introduction to programming, and life science. By the end of your chosen class, you will be proficient in the concepts covered and be ready to apply them in industrial scenarios.

So that was our compilation of some of the best free websites where you can enhance and upgrade your skills with Free Online Certifications. Hope one or more them helped you find what you were looking for.

As we come across more good sources, we will keep adding the same to this list. We will keep updating this list with more courses that may help you. Skip to content Free Courses. March 12, May 4, 5 months ago DigitalDefynd. What Is Concept Art? NET esencial. Ссылка на продолжение Courses. Are you sure? Please confirm deletion.

There is no undo! Cancel Delete. LinkedIn Learning Certificates. Stanford Certification Courses. Harvard University Free Online Courses. Free DigitalDefynd Certificate. Google Certificates. Programming Foundations: Web Security.

Introduction to Graphic Design. Managing Project Stakeholders. Time Management: Working from Home. Excel: Tracking Data Easily and Efficiently. Google Analytics for Beginners. Advanced Google Analytics. Google Analytics for Power Users.

Getting Started With Google Analytics Introduction to Data Studio. Google Tag Manager Fundamentals.

 

Browse code samples | Microsoft Docs.Microsoft SQL Server Business Intelligence Development Beginner's Guide | Packt

 

The date dimension is one of the dimensions that you will find in most of the business processes. There may be rare situations where you work with a Fact table that doesn't store date-related information. This is obvious as you can fetch all other columns out of the full date column with some date functions, but that will add extra time for processing. So, at the time of designing dimensions, don't think about spaces and add as many attributes as required.

The following diagram shows sample columns of the date dimension:. It would be useful to store holidays, weekdays, and weekends in the date dimension because in sales figures, a holiday or weekend will definitely affect the sales transactions and amounts.

So, the user will require an understanding of why the sale is higher on a specific date rather than on other days. You may also add another attribute for promotions in this example, which states whether that specific date is a promotion date or not. The date dimension will have a record for each date. The table, shown in the following screenshot, shows sample records of the date dimension:.

As you can see in the records illustrated in the preceding screenshot, the surrogate of the date dimension DateKey shows a meaningful value. This is one of the rare exceptions where we can keep the surrogate key of this dimension as an integer type but with the format of YYYYMMDD to represent a meaning as well. In this example, if we store time information, where do you think would be the place for time attributes?

Inside the date dimension? Definitely not. The date dimension will store one record per day, so a date dimension will have records per year and records for 10 years. However, 5 million records for a single dimension are too much; dimensions are usually narrow and they occasionally might have more than one million records.

So in this case, the best practice would be to add another dimension as DimTime and add all time-related attributes in that dimension. The following screenshot shows some example records and attributes of DimTime :. Usually, the date and time dimensions are generic and static, so you won't be required to populate these dimensions through ETL every night; you just load them once and then you could use them.

I've written two general-purpose scripts to create and populate date and time dimensions on my blog that you can use. The product dimension will have a ProductKey , which is the surrogate key, and the business key, which will be the primary key of the product in the source system something similar to a product's unique number. The product dimension will also have information about the product categories.

Again, denormalization in dimensions occurred in this case for the product subcategory, and the category will be placed into the product dimension with redundant values. However, this decision was made in order to avoid snow flaking and raise the performance of the join between the fact and dimensions. We are not going to go in detail through the attributes of the store dimension. The most important part of this dimension is that it can have a relationship to the date dimension. For example, a store's opening date will be a key related to the date dimension.

This type of snow flaking is unavoidable because you cannot copy all the date dimension's attributes in every other dimension that relates to it. On the other hand, the date dimension is in use with many other dimensions and facts. So, it would be better to have a conformed date dimension. Outrigger is a Kimball terminology for dimensions, such as date, which is conformed and might be used for a many-to-one relationship between dimensions for just one layer.

In the previous example, you learned about transactional fact. Transactional fact is a fact table that has one record per transaction. This type of fact table usually has the most detailed Grain. There is also another type of fact, which is the snapshot Fact table. In snapshot fact, each record will be an aggregation of some transactional records for a snapshot period of time.

For example, consider financial periods; you can create a snapshot Fact table with one record for each financial period, and the details of the transactions will be aggregated into that record. Transactional facts are a good source for detailed and atomic reports. They are also good for aggregations and dashboards. The Snapshot Fact tables provide a very fast response for dashboards and aggregated queries, but they don't cover detailed transactional records. Based on your requirement analysis, you can create both kinds of facts or only one of them.

There is also another type of Fact table called the accumulating Fact table. This Fact table is useful for storing processes and activities, such as order management. You can read more about different types of Fact tables in The Data Warehouse Toolkit , Ralph Kimball , Wiley which was referenced earlier in this chapter. We've explained that Fact tables usually contain FKs of dimensions and some measures. However, there are times when you would require a Fact table without any measure. These types of Fact tables are usually used to show the non-existence of a fact.

For example, assume that the sales business process does promotions as well, and you have a promotion dimension. So, each entry in the Fact table shows that a customer X purchased a product Y at a date Z from a store S when the promotion P was on such as the new year's sales.

This Fact table covers every requirement that queries the information about the sales that happened, or in other words, for transactions that happened. However, there are times when the promotion is on but no transaction happens! This is a valuable analytical report for the decision maker because they would understand the situation and investigate to find out what was wrong with that promotion that doesn't cause sales. So, this is an example of a requirement that the existing Fact table with the sales amount and other measures doesn't fulfill.

This Fact table doesn't have any fact or measure related to it; it just has FKs for dimensions. However, it is very informative because it tells us on which dates there was a promotion at specific stores on specific products. We call this Fact table as a Factless Fact table or Bridge table.

Using examples, we've explored the usual dimensions such as customer and date. When a dimension participates in more than one business process and deals with different data marts such as date , then it will be called a conformed dimension. Sometimes, a dimension is required to be used in the Fact table more than once. For example, in the FactSales table, you may want to store the order date, shipping date, and transaction date. All these three columns will point to the date dimension.

In this situation, we won't create three separate dimensions; instead, we will reuse the existing DimDate three times as three different names. So, the date dimension literally plays the role of more than one dimension. This is the reason we call such dimensions role-playing dimensions.

There are other types of dimensions with some differences, such as junk dimension and degenerate dimension. The junk dimension will be used for dimensions with very narrow member values records that will be in use for almost one data mart not conformed.

For example, the status dimensions can be good candidates for junk dimension. If you create a status dimension for each situation in each data mart, then you will probably have more than ten status dimensions with only less than five records in each.

The junk dimension is a solution to combine such narrow dimensions together and create a bigger dimension. You may or may not use a junk dimension in your data mart because using junk dimensions reduces readability, and not using it will increase the number of narrow dimensions.

So, the usage of this is based on the requirement analysis phase and the dimensional modeling of the star schema. A degenerate dimension is another type of dimension, which is not a separate dimension table.

In other words, a degenerate dimension doesn't have a table and it sits directly inside the Fact table. Assume that you want to store the transaction number string value. Where do you think would be the best place to add that information? You may think that you would create another dimension and enter the transaction number there and assign a surrogate key and use that surrogate key in the Fact table.

This is not an ideal solution because that dimension will have exactly the same Grain as your Fact table, and this indicates that the number of records for your sales transaction dimension will be equal to the Fact table, so you will have a very deep dimension table, which is not recommended.

On the other hand, you cannot think about another attribute for that dimension because all attributes related to the sales transaction already exist in other dimensions connected to the fact.

So, instead of creating a dimension with the same Grain as the fact and with only one column, we would leave that column even if it is a string inside the Fact table. This type of dimension will be called a degenerate dimension. Now that you understand dimensions, it is a good time to go into more detail about the most challengeable concepts of data warehousing, which is slowly changing dimension SCD.

The dimension's attribute values may change depending on the requirement. You will do different actions to respond to that change. As the changes in the dimension's attribute values happen occasionally, this called the slowly changing dimension. SCD depends on the action to be taken after the change is split in different types. In this section, we only discuss type 0, 1, and 2. Type 0 doesn't accept any changes. Let's assume that the Employee Number is inside the Employee dimension.

Employee Number is the business key and it is an important attribute for ETL because ETL distinguishes new employees or existing employees based on this field. So we don't accept any changes in this attribute. This means that type 0 of SCD is applied on this attribute. Sometimes, a value may be typed wrongly in the source system, such as the first name, and it is likely that someone will come and fix that with a change. In such cases, we will accept the change, and we won't need to keep historical information the previous name.

But the term describes analytics, in a powerful form that do. The significance of ETL in an organization is directly proportionally to how much they rely on data warehousing. The ETL tools collect, read, and migrate vast volumes of raw data from multiple data sources and across different platforms.

They load th. The sleek Steora smart bench provides a solar-powered Wi-Fi hot spot and charging stations for public spaces. Its intuitive design includes built-in sensors to regulate temperature and an automatic power-down feature in the event of heavy rain.

The Caribbean has just launched its first online database aimed at tracking human rights violations and providing data to assist advocacy work. The National Firearms Licensing Management. We cannot produce more time for ourselves. We can only improve what we do with our time. This is the essence of business technology… helping us become more efficient during our workday. Becoming more efficient is a primary objective for companies w. The database is also available as an app for smartphones.

Access to the database is free of charge for farmers who can then configu. Using dynamic third party and proprietary data sources, 25 segments have been built to give highly informative insights based on the actual behaviour and socio-economic status of a region, area unit or meshblock.

Customers can be meaningfully tagged. First, a safe bet… database as a service DBaaS will continue to grow. This useful online tool for researchers in British Columbia is unlike any digital resource found elsewhere. Two big searchable online databases provide free instant access to detailed information on 70, West Coast vessels and 58, mariners and r.

For most administrators, databases are a setup task — configured only when an application is installed and then left alone, for. These days, databases are more routinely associated with powering websites and ecommerce systems. To the casual user they look impenetrable, involving connecting to third-party database servers such as SQL and hiding behind opaque languages like PHP.

The adoption of digital tech. Is this a real thing? Part of the problem is that DARQ shares its name with a fairly recent and quite popular video game, which gets in the way of any atte. Time for action — loading customer information from a flat file into a database table with a Data Flow Task.

Time for action — looping through CSV files in a directory and loading them into a database table. Time for action — creating a data mining solution with the Microsoft Decision Tree algorithm. Time for action — finding the best mining model with Lift Chart and Profit Chart. Time for action — changing the background color of data rows based on expressions. Time for action — creating your first dashboard with PerformancePoint Dashboard Designer.

Time for action — visualizing time-based information with a scatter chart. Time for action — designing reports and working with the local processing mode. Time for action — changing a report configuration with a ReportViewer Object through code behind. All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals.

However, Packt Publishing cannot guarantee the accuracy of this information. Reza Rad has more than 10 years of experience in databases and software applications. Most of his work experience is in data warehousing and business intelligence. He has a Bachelor's degree in Computer Engineering. He has worked with large enterprises around the world and delivered high-quality data warehousing and BI solutions for them.

He has worked with industries in different sectors, such as Health, Finance, Logistics, Sales, Order Management, Manufacturing, Telecommunication, and so on. Reza has written books on SQL Server and databases.

His blog contains the latest information on his presentations and publications. Reza is a Mentor and a Microsoft Certified Trainer. He has been in the professional training business for many years. He conducts extensive handed-level training for many enterprises around the world via both remote and in-person training.

He has worked for more than 10 years with Oracle Corporation and has held various positions, including that of a Practice Manager. He had been co-running the North Business Intelligence and Warehouse Consulting practice, delivering business intelligence solutions to Fortune clients. During this time, he steadily added business skills and business training to his technical background.

In , John decided to leave Oracle and become a founding member in a small business named iSeerix. This allowed him to focus on strategic partnerships with clients to design and build Business Intelligence and data warehouse solutions. John's strengths include the ability to communicate the benefits of introducing a Business Intelligence solution to a client's architecture.

He has gradually become a trusted advisor to his clients. His philosophy is based on responsibility and mutual respect. He relies on the unique abilities of individuals to ensure success in different areas and strives to foster a team environment of creativity and achievement.

Through the years, he has worked in numerous industries with differing technologies. This broad experience base allows him to bring a unique perspective and understanding when designing and developing a data warehouse.

The strong business background, coupled with technical expertise, and his certification in Project Management makes him a valued asset to any data warehouse project. Goh Yong Hwee is a database specialist, systems engineer, developer, and trainer based in Singapore. Throughout his training, he has consistently maintained a Metrics that Matter score exceeding 8 out of He has also been instrumental in customizing and reviewing his training center's training for its clients.

When imparting knowledge, his objective has been to make technologies easy and simple for everyone to learn. His no-frills approach to training has gained him recognition over the years from both clients and employers, where his clinching of the Best Instructor Award, an accolade conferred by his employer, bore testimonial.

The dimensional model of data warehousing is optimized for reporting and analysis, so data visualization tools can directly query against the data warehouse. These models will improve data access in terms of speed and performance of queries. BI systems have one or more data visualization frontends that will be the GUI for the end user. In this book, we will go through the BI architecture and explore the Microsoft technologies that can implement and deliver BI solutions.

As the first steps, a developer needs to design the data warehouse DW and needs an understanding of the key concepts of the design and methodologies to create the data warehouse. Chapter 4, ETL with Integration Services, describes how ETL is an operation of transferring and integrating data from source systems into the data warehouse.

ETL needs to be done on a scheduled basis. Chapter 5, Master Data Management, guides readers on how to manage reference data. Chapter 6, Data Quality and Data Cleansing, explains that data quality is one of the biggest concerns of database systems. The data should be cleansed to be reliable through the data warehouse. In this chapter, readers will learn about data cleansing and how to use Data Quality Services DQS , which is one of the new services of SQL Server , to apply data cleansing on data warehouse.

In this chapter, readers will understand data mining concepts and how to use data mining algorithms to understand the relationship between historical data, and how to analyze it using Microsoft technologies. In this chapter, readers will become familiar with algorithms that help in prediction, and how to use them and customize them with parameters. Users will also understand how to compare models together to find the best algorithm for the case.

Chapter 9, Reporting Services, explores Reporting Services, one of the key tools of the Microsoft BI toolset, which provides different types of reports with charts and For More Information: www. Chapter 10, Dashboard Design, describes how dashboards are one of the most popular and useful methods of visualizing data.

In this chapter, readers will learn when to use dashboards, how to visualize data with dashboards, and how to use PerformancePoint and Power View to create dashboards.

Chapter 11, Power BI, explains how predesigned reports and dashboards are good for business users, but power users require more flexibility.

Power BI is a new self-service BI tool. Chapter 12, Integrating Reports in Applications, begins with the premise that reports and dashboards are always required in custom applications. NET applications in web or Metro applications to provide reports on the application side for the users.

Data visualization is all about displaying analytical information that is processed in an OLAP cube or a tabular model based on the logical design of data model there are some scenarios where visualization will be done directly out of a data warehouse, and not the cube or BISM.

Analytical information can be presented in many ways: grids, charts, static and dynamic reports, dashboards, or any feature that helps users to understand data and numbers in the best way. The only downside of it is the development time. In this chapter, you will learn about PerformancePoint, which is a part of the SharePoint product. To install PerformancePoint, you need to install SharePoint rst. This means that you cannot install PerformancePoint on a nonserver operatng system because a SharePoint server can only be installed on a server operatng system.

Finally, you can create the Business Intelligence site where you can design dashboards using Dashboard Designer, and deploy them onto the BI site. In the following sectons of this chapter, we will go through each of these steps to illustrate how to create and design dashboards using PerformancePoint Dashboard Designer.

For all PerformancePoint examples in this chapter, you will need an operatng system server editon to be able to install SharePoint and congure PerformancePoint on it. In this book, we used Windows Server and SharePoint These steps are a prerequisite for other samples in PerformancePoint.

For this example, Windows Server must be installed. Installaton of SharePoint is not explained in this book SharePoint conguraton and installaton requires another book in itself. So, let's get started with the conguraton using the following steps: 1. Then, go to the PerformancePoint Service Applicaton Set ngs page and use the Unatended Service Account opton map it to a domain account on an actve directory.

Please note that to get this step working, you may rst need to congure Secure Store Service Applicaton. Next, go back to Central Administraton. In the template selecton secton, under Enterprise, choose Business Intelligence Center, as shown in the following screenshot: For More Information: www. The rst three steps of this example explained how to enable the PerformancePoint service applicaton.

To use the PerformancePoint service, you must have an actve directory account to use as unatended service account. In the next steps, you learned how to create Business Intelligence Center-based site collecton.

Note that if you want to create PerformancePoint dashboards and deploy them, you need to have a Business Intelligence site collecton. In the next examples, we will go through working with Dashboard Designer. To create and design dashboards, another utlity from SharePoint named Dashboard Designer exists. Dashboard Designer is the other compartment of PerformancePoint and is the development studio for dashboards. In this secton, you will learn how to work with Dashboard Designer, and you will learn about its main components.

Time for action creating your rst dashboard with PerformancePoint Dashboard Designer Afer creatng the BI site collecton, it is the tme to create dashboards with Dashboard Designer. In this example, we will see how we can open Dashboard Designer, which is the designer tool for PerformancePoint. Then, we will connect to an analysis service cube. Afer that, we will create a very simple dashboard from measures and dimensions. Perform the following steps to create a dashboard: 1.

An applicaton will be launched for the rst tme, it may take longer. You will then see that Dashboard Designer is open, as shown in the following screenshot: For More Information: www.

The new data source will be created under data connectons, and the Propertes window will be opened in the main pane of Dashboard Designer. Right-click on the data source and rename it to Sal es Summar y Cube Connect i on. Leave the other conguratons as default and test the data source. The Create an Analytc Chart dialog box will appear and ask for data source connecton; choose Sales Summary Cube Connecton under the data connectons and click on Finish.

Name the new report Sal es by Ter r i t or y. You will see the Report Designer opton in the main pane. You will also see the list of measures, dimensions, and Named Sets coming from cube in the right-hand side pane of the Details pane. Go to the Details pane again and drag-and-drop the Calendar hierarchy under the Date dimension in the Calendar folder of the Botom Axis secton.

Drag-and-drop the Sales Territory hierarchy from the Details pane in the Sales Territory dimension of the Series secton.

You will see a column chart appear in the main report designer, which shows the total sales for all territories over a period.

Click on all the Sales Territory optons in the Series legend and you will see that a chart is drilled down to geographical groups. Click on All Periods, and you will see that the chart will create columns for each calendar year as shown in the following screenshot: What just happened? You made your rst PerformancePoint dashboard in Dashboard Designer just now. As you saw, it was just as easy as dragging-and-dropping measures and dimensions.

Now, let's go through each step and take a closer look at what we did in this example. The two main components of a PerformancePoint dashboard are: data sources and PerformancePoint contents. They contain charts, grids, dashboard pages, lters, and content related to dashboards.

The rst step to creatng a dashboard is to create a data source. In this example, we created a connecton to Sales Summary Cube in Analysis Services as shown in the steps 4 to 7. Report is one of the main contents of PerformancePoint, which can visualize data in analytcal-chart type dened in step 9 and grid or other types, which will be discussed later.

A report needs a data source to work with we set a data source for the report in step The Report designer window is a simple designer that contains data source enttes in the Details pane on the right-hand side. A report itself is shown in the main pane; this report displays the main components at the botom in this case: Series, Botom Axis, and Background. The default chart type in PerformancePoint is the Column chart, which can be changed we will go through that in the next examples.

Steps 12 to 16 showed how simple it is to create a column chart report based on the sales amounts in territories and calendars. One of the main advantages of PerformancePoint reports is that it is well junctoned with analysis services hierarchies. In this example, in steps 17 and 18, you saw how easy it is to drill down to the rst level of each hierarchy with a simple click on the root. The dashboard pages In the previous secton, you learned about how to create reports in PerformancePoint.

In this secton, you will learn about dashboard pages. A report or chart is not viewable in SharePoint, since the SharePoint site does not work with web pages. So, you would need to create a web page that contains one or more reports; such web pages are called dashboards in PerformancePoint. Time for action creating a dashboard page In this example, we will create a dashboard page. We will add the report from the previous example to it and then we will deploy the dashboard to the SharePoint site with the help of the following steps: 1.

Rename the dashboard to Sal es Dashboar d. In the main pane of Dashboard Designer, you will see the name of the web page, which by default is set as Page 1; change it to Sales. In the right-hand side pane the Detail pane , you will see PerformancePoint's contents, such as Scorecards, Reports, and Filters, listed. Click on Expand Reports, expand PerformancePoint Contents, and under it you will see the report Sales by Territory that was designed in the previous example.

Drag-and-drop the Sales by Territory report into the Dashboard Content pane this pane is located in the main pane of the botom secton.

Right-click on the Sales Dashboard opton in Workspace Browser and choose Deploy to SharePoint, as shown in the following screenshot: 8. In the Deploy to BI site dialog box, leave the default conguraton as is and deploy it to the dashboar ds folder as it is by default.

A few moments later, you will see the Dashboard page deployed to the SharePoint site and showed to you in the browser. The Dashboard page contains the Sales by Territory report. Now, we want to create a quick link for the Dashboard page and copy the URL from the open web browser. Click on that. Click on the Add link buton. The Add a Link window will be opened. Enter Sal es, and in the address box, paste the address that you've copied from the web page previously.

Save the link. Now, you will see the Sales link in the lef-hand side of your BI website. This link will be durable through most of the pages in this website; it provides easy and quick access to the Dashboard page, as shown in the following screenshot: What just happened? In this secton, you learned how to create a dashboard page steps 1 to 4. Each dashboard can contain one or more pages. The dashboard that we created in this example had just one page. The architecture shown in the preceding diagram contains components that are common in most of the BI systems.

In the following sections, you will learn more about each component. The data warehouse is the core of the BI system. A data warehouse is a database built for the purpose of data analysis and reporting. This purpose changes the design of this database as well. As you know, operational databases are built on normalization standards, which are efficient for transactional systems, for example, to reduce redundancy.

As you probably know, a 3NF-designed database for a sales system contains many tables related to each other. So, for example, a report on sales information may consume more than 10 joined conditions, which slows down the response time of the query and report.

A data warehouse comes with a new design that reduces the response time and increases the performance of queries for reports and analytics. You will learn more about the design of a data warehouse which is called dimensional modeling later in this chapter. So there is a requirement for data consolidation that extracts data from different sources and transforms it into the shape that fits into the data warehouse, and finally, loads it into the data warehouse; this process is called Extract Transform Load ETL.

There are many challenges in the ETL process, out of which some will be revealed conceptually later in this chapter. According to the definition of states, ETL is not just a data integration phase. Let's discover more about it with an example; in an operational sales database, you may have dozen of tables that provide sale transactional data.

When you design that sales data into your data warehouse, you can denormalize it and build one or two tables for it.

So, the ETL process should extract data from the sales database and transform it combine, match, and so on to fit it into the model of data warehouse tables.

There are some ETL tools in the market that perform the extract, transform, and load operations. SSIS also has many built-in transformations to transform the data as required.

A data warehouse is designed to be the source of analysis and reports, so it works much faster than operational systems for producing reports. However, a DW is not that fast to cover all requirements because it is still a relational database, and databases have many constraints that reduce the response time of a query.

The requirement for faster processing and a lower response time on one hand, and aggregated information on another hand causes the creation of another layer in BI systems.

This layer, which we call the data model, contains a file-based or memory-based model of the data for producing very quick responses to reports. Microsoft's solution for the data model is split into two technologies: the OLAP cube and the In-memory tabular model. The OLAP cube is a file-based data storage that loads data from a data warehouse into a cube model.

The cube contains descriptive information as dimensions for example, customer and product and cells for example, facts and measures, such as sales and discount. The following diagram shows a sample OLAP cube:. In the preceding diagram, the illustrated cube has three dimensions: Product , Customer , and Time. Each cell in the cube shows a junction of these three dimensions.

Aggregated data can be fetched easily as well within the cube structure. For example, the orange set of cells shows how much Mark paid on June 1 for all products.

As you can see, the cube structure makes it easier and faster to access the required information. Multidimensional modeling is based on the OLAP cube and is fitted with measures and dimensions, as you can see in the preceding diagram. The tabular model is based on a new In-memory engine for tables. The In-memory engine loads all data rows from tables into the memory and responds to queries directly from the memory. This is very fast in terms of the response time. The frontend of a BI system is data visualization.

In other words, data visualization is a part of the BI system that users can see. There are different methods for visualizing information, such as strategic and tactical dashboards, Key Performance Indicators KPIs , and detailed or consolidated reports.

As you probably know, there are many reporting and visualizing tools on the market. Microsoft has provided a set of visualization tools to cover dashboards, KPIs, scorecards, and reports required in a BI application. SSRS is a mature technology in this area, which will be revealed in. Chapter 9 , Reporting Services.

Excel is also a great slicing and dicing tool especially for power. There are also components in Excel such as Power View, which are designed to build performance dashboards.

You will learn more about Power View in Chapter 9 , Reporting. Sometimes, you will need to embed reports and dashboards in your custom written application. Chapter 12 , Integrating Reports in Application , of this book explains that in detail. Master Data Management Every organization has a part of its business that is common between different systems. For example, an organization may receive customer information from an online web application form or from a retail store's spreadsheets, or based on a web service provided by other vendors.

Microsoft's solution for MDM is Master. Data Services MDS. Master data can be stored in the MDS entities and it can be maintained. Even if one or more systems are able to change the master data, they can write back their changes into MDS through the staging architecture. The quality of data is different in each operational system, especially when we deal with legacy systems or systems that have a high dependence on user inputs.

As the BI system is based on data, the better the quality of data, the better the output of the BI solution. Because of this fact, working on data quality is one of the components of the BI systems. As an example, Auckland might be written as "Auck land" in some Excel files or be typed as "Aukland" by the user in the input form. There are also matching policies that can be used to apply standardization on the data.