Professional Microsoft SQL Server 2012 Integration Services

---

Erik rated it really liked it Aug 11, Sudhir rated it it was ok Jul 04, Sam rated it it was amazing May 01, Caesar Moussalli rated it really liked it Aug 03, Jeff rated it it was amazing Apr 12, Mncockerham rated it it was ok Feb 04, Aaron Varner rated it it was amazing Sep 19, Drew Lackovic rated it liked it Feb 19, Pete Fuller rated it it was amazing Feb 15, Spetz rated it liked it Nov 23, Jennifer Guyler rated it liked it Nov 24, Evelyn Dickinson rated it really liked it Sep 08, Emily rated it liked it Apr 26, Jquick1us rated it it was amazing Oct 01, Paulo Henrique rated it it was amazing Jun 07, Steven rated it really liked it Sep 02, Antonios rated it it was amazing May 12, Dhanam rated it really liked it Dec 21, Michael Thorp rated it really liked it Nov 01, Rene Leupold rated it liked it Jan 06, There are no discussion topics on this book yet.

If you like books and love to build cool products, we may be looking for you. Brian is a contributing columnist for many industry magazines and sites. He has co-authored and authored more than 9 SQL Server books. There is more than one author in the GoodReads database with this name. You will also learn how to build dashboards on the website, and how to work with Mobile Apps for Apple, Android and Windows Phone.

Visualization is an important part of any BI system. In Power BI, Visualization plays a critical part. In this section, you will learn about why visualization is important, with few basics of visualizations such as comparing stacked vs. The importance of slicing and dicing data in Power BI is critical. Power BI is not a visualization tool only, but it is also a data exploration tool. There are several ways you can filter the data. In this section, you will learn the difference between filters and slicers. You also learn about different scopes of filtering, as well as filtering modes.

For slicers, you will learn different types of slicers and some advanced features such as syncing slicers through different pages. Know that you know about visualizations and slicing and dicing, it is a good time to talk about some advanced techniques which will take your visualizations to the next level in Power BI. You will learn about techniques such as changing the interaction of visuals, report page tooltips, Bookmarks and dynamic visualizations in this section.

It is a good time to learn about all built-in visuals in Power BI now. It is important to know which visual should be used in what scenario.

You will also learn in this section about the pros and cons of each visual. You will learn specific features of the visual that can help to solve real-world scenarios. All the examples will be hands-on. In Power BI, there are multiple ways of visualizing items on the map.

RADACAD Blog

In this section, you will learn about all the built-in ways of using map visuals in Power BI, the pros, and cons of each method and special considerations for some of the visuals. In addition to the built-in list of Power BI visuals, you can leverage some of the third party visuals created by other companies called Custom Visuals. You will learn about the most useful custom visuals in Power BI through many demos.

Power BI is the newest Microsoft BI tool for data mash up, build modeling, and visualize it effectively. There are some myths about Power BI that sometimes prevents people and organization to move towards using this product. Please note that these are Myths, and they are not the right assumptions.

There are many scenarios that Power BI has been used in enterprise solutions. Power BI features for data mash up with the very powerful data transformation component: We have designed, implemented and have seemed many BI enterprise solutions based on Power BI within very large organizations. Power BI is an easy to use tool, but for basic functions. Every BI application requires advanced data transformations which need to be handled with Power Query M scripting language.

See a Problem?

Designing and implementing solutions with Best Practices is always a requirement for reliable BI applications. Power Query is the core of data extraction in Power BI. Power Query supports a wide range of data sources. There is also the possibility to connect to many systems such as Salesforce. In fact, the reverse is true. Power BI is such powerful that can be the replacement of many other expensive BI tools in the market. Power BI has 5 powerful components that cover main aspects of BI and data analysis system.

In addition, there is always the possibility to use this as a hybrid approach and save lots of time and money along with great features that are only available in this product. I spent probably about two weeks looking for a good Microsoft Power BI class that would cover all of the aspects of the program. I wanted to walk away from the class being able to apply what I learned immediately.

Most training companies that I looked into were in a state of flux with Power BI mostly due to the transitions that Power BI itself was going through. The class outline seemed to include every topic on my checkoff list plus much more. I decided to give Reza a try. Reza completely lived up to his hype. He took us through a natural progression of the software, using example after example of how to complete a task.

We went through real world scenarios, a bare minimum of two scenarios for each minor topic. I was completely impressed with his Power BI knowledge, understanding and abilities. Any question we came to Reza with was answered completely and with even more examples. After the class, my goal of immediately applying what I learned was attained. Right away I was able to successfully pull and massage data, create useful reports and post them to dashboards.

I learned a lot from this course: And Reza is a masterful user of this tool.

Module 1: Power BI for Data Scientists – 2 days course

Note that Reza covers a lot of ground in this course, and it is pretty fast paced. Reza took the group through all the components that make up environment. He explained how they had evolved and took the group through walk-throughs of each one. Reza was great an answering questions from the audience at the event and going into extra detail if necessary. When Reza worked on our project, nothing phased or flustered him, he always came up with solutions for problems that seemed to me as insurmountable.

I had a call with Reza who made my life so much easier in just under an hour!

Any time spent speaking to Reza will be well worth it — I have saved hours of trying to get my head around our dashboards by getting some very useful tips and explanations on why things are done the DAX way! Not only that but he is very patient and straight forward. The course was an excellent investment overall, it exceed my expectations. It was well paced and presented. The instructor, Reza Rad, was excellent and was able to answer all my questions and explain complex idea in a manner that was easy to understand and follow.

I had been using Power BI Desktop for a number of months prior to taking this course, but wish I had attended it sooner! The course structure of 1 day of overall Power BI and followed by 4 days of more intensive instruction on the various parts of Power BI allowed for a basic understanding of the whole, and then more comprehensive learning.

The live-on-line experience worked well technically and allowed for questions and problem-solving with the instructor. I learned a lot about Power BI and this course gave me a great foundation for using Power BI to clean, model, design, and share reports using a variety of visualizations that will provide business intelligence to my company. I would recommend this course to anyone wanting to learn Power BI either as a starting point or even after you have used the tool to deepen your understanding and build your skill-set.

Reza Rad reza radacad. This training is designed for data wrangler, data developer or data transformer, who have the raw data coming from one or more data sources and want to make it ready for further modeling and analytics. In this training, you will learn detailed data transformation practices of Power BI using Power Query.

In this course, you will learn all things about Power Query, from zero to hero. You will learn Power Query from basic level with Getting data from different data sources. You will learn about different types of transformations available in Query Editor. Table transformations such as Pivot and Unpivot will be discussed, as well as specific column transformations such as date column transformations. Unique features such as error handling, generators, structured columns, custom functions and many other advanced level features of Power BI data transformations will be explored through hands-on labs and lecture.

After this course, you will be able to implement any types of data transformation through Power Query in Excel or Power BI. You will be able to work through your raw data and make it ready for modeling and analytics. In this section, you will learn about Power Query basics which starts with Getting data. You will learn different parts of the Query Editor through an example of using Power Query to transform a dataset. Before going any further in learning Power Query, you need to understand about data structures and data types. There are three main data structures in Power Query; table, record, and list.

You will learn about these types through an example of getting data from a JSON structure. You will also learn about data types and their differences. One of the most common data transformations is combining datasets.

Depends on the types of datasets and the way that they are related to each other, you may want to merge or append them. In this section, you will learn why you need to combine data at first, and then you will learn about scenarios that you combine data in Power Query. To get the best experience with Power Query Editor, you need to consider organizing your queries and steps in the right way. In this section, you will learn about actions you can do on steps, such as moving them up or down, splitting steps in a query, etc. You will also learn about organizing your queries in groups folders. Filtering rows in Power Query is an important transformation especially when the dataset is big, or when the data needs to be cleaned.

There are different ways of doing filtering in Power Query. You will learn about ways to remove some rows from the top or bottom of the table, and ways that you can filter a data table based on criteria. You will learn about basic filtering and the difference of that with the advanced filtering, and potential challenges that you may have through this process.

In this section, you will learn actions that you can do on columns, and what are best practices to make sure you have the best performance in your Power BI model considering columns in your tables. You will also learn about some generic column operations and transformations. Some of the most important table transformations will be explained in this section. You will learn about a way to change the granularity of a table; Grouping. You will also learn scenarios that grouping data can be more than a simple transformation.

You will learn about transformations such as Transpose, Pivot and Unpivot, and the difference of all these items with scenarios of using it on real-world datasets. When you work with text values, there are many transformations you can apply. Transformations such as a split column, removing part of a text, or adding a prefix or postfix to it, concatenating some columns together, etc. You will learn in this section how to do numeric transformations.

We will talk about standard transformations such as divide and integer-divide. You will also learn about transformations such as rounding, statistics transformations, and even some scientific transformations and use cases for those items. There are many transformations applicable to date and time columns. You may want to fetch year part of a date or get the fiscal calculation of a date. You may want to calculate age based on the birthday or calculate the difference between two dates.

You will learn all these items in this section, you will also learn about time zone consideration when working with current date and time in Power BI, and how you can resolve it in Power Query. When you combine tables, you get a structured column as a result, which can be a table, list, or record in every value. There are several transformations you can apply on structured columns, which you will learn in this section. You will also learn what may be the potential issue with some of these transformations.

There are two types of transformations in Power Query; Transforming an existing column, or adding a column based on a transformation. In this section, you will learn about these two types, their differences, and few other transformations that we have available in the add column tab of the Power Query Editor through some examples. Power Query is a powerful tool for data transformation. This power can be amplified even more if you can make your queries dynamic.

Instead of repeating several steps for similar data sources, you can create a function from those steps, and run that function for all other sources. Functions get parameters as the input. Functions and parameters can make everything in Power Query dynamic. If you want to learn Power Query advanced deep dive, this is the section to go through.

If you want to be a good data wrangler or data developer with Power Query, you must learn M scripting. The good news is that M scripting is not a hard language to learn.

SQL Server Integration Services

As you are dealing with data in Power Query, it is important to learn how to work with table, list, and record from the code. In this section, you will learn about these three structures in code, and how to navigate between different parts of each structure. Now that you know more about M scripting, it is time to see how powerful this part of Power Query can be compared to the graphical interface of query editor. In this section, you will learn features that you have access to apply using M scripting. You will learn ways to get a list of all functions, doing error handling in an advanced way.

Applying some changes in functions and parameters which is only possible through the code. You will also learn an end-to-end example using everything you learn about M at the end. Some transformations or operations needs careful attention in Power Query. In this section, you will learn about performance tips and trick for Power Query to make sure you have always a well performance tuned data transformation logic.

Each sample will be discussed through the live demo in this section. In any data related solution, you should expect bad data rows to appear. This section is all about how to handle errors, deal with bad data rows, create troubleshooting reports, etc. At the end of the training, we go through some end-to-end solutions using Power Query.

These solutions leverage everything you learned through the training about this tool and language; you will see how all those parts come to help together to build the solution. We will go through building a date dimension which has all calendar columns, fiscal columns, and public holidays fetched live, and we will talk about combining files from a folder. The well-known worldwide training in Microsoft Advanced Analytics field on the planet from one to seven days of training delivered by the well-known experts and MVPs, authors of books, and speakers of many conferences themselves.

In this training course, you will learn some basic concepts for Machine Learning, Predictive and Descriptive analytics. You learn how to write R codes for the aim of data wrangling, data modeling, data visualization, and machine learning. Moreover, you will learn how to use custom AI tools like Azure Machine learning for creating your desire model, deploy it and use it as web service in other applications and scenarios like the Internet of Things IoT.

You will learn about how to use R in a dashboard, how to R in the cloud and on-premises storage. You will learn how to use pre-build AI tools like Bot and cognitive services to create smart report and applications. If you are a data scientist, data analyst, business intelligence developer, or data architect, this course has many things to teach you all.

This training is designed for data scientists, data developer or data architecture, who have the data in the cloud or thinking about using Microsoft machine learning tools in cloud scale. In this training, you will get familiar with machine learning cloud possibilities. In this course, you will learn how to Azure ML Studio as the first tool for machine learning cloud that introduced in The detail on how to create a model, how to enhance machine learning algorithms, how to import data and so forth will be explained.

Then, you will get familiar with Azure Data Science Virtual Machine as a comprehensive tool for machine learning, some of the tools in it like the Tensor flow and Azure ML workbench will be explained. Then, how to do machine learning in Azure Data Lake store will be explained. Finally, Azure Data Bricks and how to use it for the aim of machine learning will be explained too.

This training has many hands-on labs, and all the required scenario will be explained step by step. At the end of this training, the audience will learn how to define a machine learning problem and how to use Azure ML Studio for cloud machine learning, and also how to use Azure data Lake Analytics, Azure Data Bricks and so forth for machine learning.

In this section, you will learn some basic of machine learning and how it works. Then some introduction to Azure ML Studio will be provided. It has much popular data science and other tools pre-installed and pre-configured to jump-start building intelligent applications for advanced analytics. It is available on Windows Server and Linux. In this session, the audience will learn. Azure Data Lake Analytics is a distributed, cloud-based data processing architecture offered by Microsoft in the Azure cloud.

It is an on-demand analytics job service that simplifies big data. Instead of deploying, configuring, and tuning hardware, you write queries to transform your data and extract valuable insights. The analytics service can handle jobs of any scale instantly by setting the dial for how much power you need. You only pay for your job when it is running, making it cost-effective.

In this section, you will learn. Azure Databricks is an Apache Spark-based analytics platform optimized for the Microsoft Azure cloud services platform. Designed with the founders of Apache Spark, Databricks is integrated with Azure to provide one-click setup, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts. Azure data bricks are one of the main platforms for the aim machine learning in this part audience will get familiar with.

This training is designed for data science, data analysis and who want to do machine learning by writing R or Python code. This course will start with some explanation of different machine learning algorithms and approaches. Then, some discussion on basic statistical analysis will be provided such as probability, factor analysis, hypothesis testing and so forth.

Then the process of machine learning from business understanding, data cleaning, feature selection, model selection, split data for testing and training, evaluating the created model and finally developing and visual the trained model and analyzing the result will be presented. For predict analysis algorithms such as decision tree, boosted decision tree, decision forest will be explained. The concept and how they work will be explained. Then how to set parameters for each of them will be illustrated.

Also, the process of data preparation for each of these algorithms will be discussed. Finally, the related code for writing this algorithm in the cloud will be explained. The same process will be done for the descriptive algorithms such as clustering. In this two days training, the audience will learn some deep concepts for machine learning, data analysis, main algorithms for predictive, descriptive and statistical analysis using R, R in Power BI and SQL Server. The main concepts, life cycle and best practice of doing machine learning with Microsoft product will be explained.

In this section, the audience will learn some of the algorithms such as Decision tree, Decision Forest, regression and SVM for the aim of predictive analytics. The main concepts of these algorithms will be explained, and the related R or Python code will be shown. How to analysis the trained model and set up the parameters also will be discussed. Finally, how to evaluate the result will be explained. Descriptive analytics is an unsupervised learning approach. In this part, the audience will be familiar with some of the main algorithms for descriptive analytics from text mining, clustering and, Market basket analytics.

Forecasting is one of the main approaches for time series. The main concepts of the time series will be explained and how to decompose time series, how to use exponential smoothing and ARIMA for forecasting the time series data.

Get SQL Server Integration Services

This training is designed for data modeler, who have the data prepared to be modeled for analysis. Usually, people who attend this training needs to attend module 2 beforehand to learn about the step before the modeling. In this two days training, you will learn DAX from zero to hero. You will learn how to design the best model in Power BI with relationships, considering formatting and data types. You will learn from Simple DAX calculations to complex expressions and calculations for solving real-world challenges of a BI solution.

The training continues with more focus on DAX; we will talk about the evaluation context in DAX, which defines the mindset and the way of thinking when you are writing DAX expressions. You will learn about DAX function categories such as Aggregation functions, Iterators, Filter functions, parent-child functions, time intelligence functions, functions dealing with relationships, etc. You will learn all scenarios through hands-on examples of real-world data.

At the end of this training, you will be able to design the proper data model in Power BI, understand all relationship requirements and implement the right relationship, write complex DAX expressions for your analytics need, and put them all together to build the best model for your data analysis solution using Power BI. Power BI uses the in-memory engine, named xVelocity. The in-memory engine of Power BI makes the analysis super-fast.

Everything will respond very fast in this model. In this section, you will learn about the basics of the modeling engine and some of the differences of that with SSAS and Power Pivot. This is the expression language in Power BI for analytics. DAX is a dynamic expression language which will consider the interaction of the user at the time of visualization.

Using DAX, you can do calculations such as year to date, year over year comparison, etc. Most of the data modeling training is about DAX. In this section, you will learn the basics of DAX. There are three types of calculations in Power BI. Calculated Column, Measure, and Calculated Table. You can write DAX expression in all these three types of objects. This section will teach you what the main difference between the calculated column, measure, and the calculated table is, and what are scenarios of using them.

The first set of important functions in DAX are aggregation functions. The way of working with iterators is different. Iterators get an input table and an expression. Example of iterator function is SUMX. Filter functions are probably the most important functions in DAX.

Book Published: Microsoft SQL Server Integration Services: An Expert Cookbook | RADACAD

You can refer to a column in DAX like Excel , but you cannot refer to rows. If you want to refer to rows in an expression, you must filter it, and that is why Filter functions are important. There are several filter functions, and the behavior of all of them are unique. In this section, we will talk about some of these functions through real-world examples.

Understanding Evaluation contexts are one of the most critical learnings in DAX. There are two types of contexts; Row context, and filter context.

In this section, you will learn about the difference of all these, and you will learn scenarios that you need to be careful when the context changes. Some other functions change the behavior of relationship such as UseRelationship function. In this section, you will learn about relationship functions in DAX and scenarios of using them. Calculations based on time and date are critical for many businesses such as finance. You can use DAX to do calculations such as year to date, fiscal year to date, year over year comparison, and rolling 12 months average. In this section, you will learn some basic time intelligence functions such as TotalYTD to a calculated year to date.

You will also learn about scenarios when you do not have the built-in function for your use case and will learn how to write the combination of function usages in DAX to achieve the solution. However, you can take a step further, and make the expression of DAX even more dynamic. The user can change a value which is defined statically in your DAX expression using a parameter. Parameters will make your DAX expressions even more dynamic. In this section, you will learn about parameters, and their usages, and the scenario of using a parameter table to select from multiple measures dynamically.

DAX can navigate through a hierarchy with an unknown number of levels. Example of such a hierarchy is a chart of accounts or organizational hierarchy. In this section, you will learn about parent-child functions which can be used for organization hierarchy. You will learn different scenarios of using these functions in real-world examples. Performance considerations when doing the modeling in Power BI is the last but not least important part of this course.

• Airing Grandmas Laundry
• The ACT Boost
• Os Políticos e a Crise - De Salazar a Passos Coelho (Portuguese Edition)
• The Family Model: Managing the impact of parental mental health on children
• The Other Side of Time
• Metatron Questo E IL Fervido Appello (Italian Edition)
• Afraid To Get Help Getting Out Of Debt? - Simple to Use Idea Guide for the Frustrated, Fearful & Faint-Hearted