Oracle, MySQL, Cassandra, Hadoop Database Training Classes in Dearborn Heights, Michigan

Learn Oracle, MySQL, Cassandra, Hadoop Database in Dearborn Heights, Michigan and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current Oracle, MySQL, Cassandra, Hadoop Database related training offerings in Dearborn Heights, Michigan: Oracle, MySQL, Cassandra, Hadoop Database Training

We offer private customized training for groups of 3 or more attendees.

Oracle, MySQL, Cassandra, Hadoop Database Training Catalog

cost: $ 495length: 1 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1090length: 3 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 1090length: 2 day(s)

Cassandra Classes

Hadoop Classes

cost: $ 1590length: 3 day(s)

Linux Unix Classes

cost: $ 1890length: 3 day(s)

Microsoft Development Classes

MySQL Classes

cost: $ 490length: 1 day(s)
cost: $ 790length: 2 day(s)
cost: $ 1290length: 4 day(s)
cost: $ 1190length: 3 day(s)

Oracle Classes

cost: $ 2090length: 5 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 1190length: 3 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 1590length: 4 day(s)
cost: $ 790length: 2 day(s)
cost: $ 690length: 1 day(s)
cost: $ 2800length: 5 day(s)
cost: $ 1690length: 3 day(s)
cost: $ 2600length: 5 day(s)

SQL Server Classes

cost: $ 1290length: 3 day(s)
cost: $ 890length: 2 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2090length: 4 day(s)
cost: $ 2090length: 5 day(s)
cost: $ 2190length: 5 day(s)
cost: $ 1290length: 3 day(s)

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Gain insight and ideas from students with different perspectives and experiences.

Blog Entries publications that: entertain, make you think, offer insight

The original article was posted by Michael Veksler on Quora

A very well known fact is that code is written once, but it is read many times. This means that a good developer, in any language, writes understandable code. Writing understandable code is not always easy, and takes practice. The difficult part, is that you read what you have just written and it makes perfect sense to you, but a year later you curse the idiot who wrote that code, without realizing it was you.

The best way to learn how to write readable code, is to collaborate with others. Other people will spot badly written code, faster than the author. There are plenty of open source projects, which you can start working on and learn from more experienced programmers.

Readability is a tricky thing, and involves several aspects:

  1. Never surprise the reader of your code, even if it will be you a year from now. For example, don’t call a function max() when sometimes it returns the minimum().
  2. Be consistent, and use the same conventions throughout your code. Not only the same naming conventions, and the same indentation, but also the same semantics. If, for example, most of your functions return a negative value for failure and a positive for success, then avoid writing functions that return false on failure.
  3. Write short functions, so that they fit your screen. I hate strict rules, since there are always exceptions, but from my experience you can almost always write functions short enough to fit your screen. Throughout my carrier I had only a few cases when writing short function was either impossible, or resulted in much worse code.
  4. Use descriptive names, unless this is one of those standard names, such as i or it in a loop. Don’t make the name too long, on one hand, but don’t make it cryptic on the other.
  5. Define function names by what they do, not by what they are used for or how they are implemented. If you name functions by what they do, then code will be much more readable, and much more reusable.
  6. Avoid global state as much as you can. Global variables, and sometimes attributes in an object, are difficult to reason about. It is difficult to understand why such global state changes, when it does, and requires a lot of debugging.
  7. As Donald Knuth wrote in one of his papers: “Early optimization is the root of all evil”. Meaning, write for readability first, optimize later.
  8. The opposite of the previous rule: if you have an alternative which has similar readability, but lower complexity, use it. Also, if you have a polynomial alternative to your exponential algorithm (when N > 10), you should use that.

Use standard library whenever it makes your code shorter; don’t implement everything yourself. External libraries are more problematic, and are both good and bad. With external libraries, such as boost, you can save a lot of work. You should really learn boost, with the added benefit that the c++ standard gets more and more form boost. The negative with boost is that it changes over time, and code that works today may break tomorrow. Also, if you try to combine a third-party library, which uses a specific version of boost, it may break with your current version of boost. This does not happen often, but it may.

Don’t blindly use C++ standard library without understanding what it does - learn it. You look at std::vector::push_back() documentation at it tells you that its complexity is O(1), amortized. What does that mean? How does it work? What are benefits and what are the costs? Same with std::map, and with std::unordered_map. Knowing the difference between these two maps, you’d know when to use each one of them.

Never call new or delete directly, use std::make_unique and [cost c++]std::make_shared[/code] instead. Try to implement usique_ptr, shared_ptr, weak_ptr yourself, in order to understand what they actually do. People do dumb things with these types, since they don’t understand what these pointers are.

Every time you look at a new class or function, in boost or in std, ask yourself “why is it done this way and not another?”. It will help you understand trade-offs in software development, and will help you use the right tool for your job. Don’t be afraid to peek into the source of boost and the std, and try to understand how it works. It will not be easy, at first, but you will learn a lot.

Know what complexity is, and how to calculate it. Avoid exponential and cubic complexity, unless you know your N is very low, and will always stay low.

Learn data-structures and algorithms, and know them. Many people think that it is simply a wasted time, since all data-structures are implemented in standard libraries, but this is not as simple as that. By understanding data-structures, you’d find it easier to pick the right library. Also, believe it or now, after 25 years since I learned data-structures, I still use this knowledge. Half a year ago I had to implemented a hash table, since I needed fast serialization capability which the available libraries did not provide. Now I am writing some sort of interval-btree, since using std::map, for the same purpose, turned up to be very very slow, and the performance bottleneck of my code.

Notice that you can’t just find interval-btree on Wikipedia, or stack-overflow. The closest thing you can find is Interval tree, but it has some performance drawbacks. So how can you implement an interval-btree, unless you know what a btree is and what an interval-tree is? I strongly suggest, again, that you learn and remember data-structures.

These are the most important things, which will make you a better programmer. The other things will follow.

Here is a list of the organizations that use Python. This list is periodically updated by HSG’s software fans as well as the community at large.
 

Web Development

1.       Yahoo Maps
Yahoo acquired Four11, whose address and mapping lookup services were implemented in Python. Yahoo Maps still uses Python today, as can be seen by examining its URLs.
 

2.       Yahoo Groups
A comprehensive public archive of Internet mailing lists that was originally implemented in pure Python. At one point Scott Hassan, one of the founders of Findmail/eGroups (the company that was later acquired by Yahoo), reported that they had 180,000 lines of Python underlying everything from their 100% dynamic website to all email delivery, pumping out 200 messages/second on a single 400 MHz Pentium.

 

data dictionary workThe mainstay of a corporation is the data that it possesses. By data, I mean its customer base, information about the use of its products, employee roles and responsibilities, the development and maintenance of its product lines, demographics of supporters and naysayers, financial records, projected sales ... It is in the organization of this data that advancements to the bottom line are often realized i.e. the nuggets of gold are found. Defining what is important, properly cataloging the information, developing a comprehensive protocol to access and update this information and discerning how this data fits into the corporate venacular is basis of this data organization and may be the difference between moving ahead of the competition or being the one to fall behind.

Whenever we attempt to develop an Enterprise Rule Application, we must begin by harvesting the data upon which those rules are built. This is by no means an easy feat as it requires a thorough understanding of the business, industry, the players and their respective roles and the intent of the application. Depending upon the scope of this undertaking, it is almost always safe to say that no one individual is completely knowledgeable to all facets needed to comprise the entire application.data dictionary

The intial stage of this endeavor is, obviously, to decide upon the intent of the application. This requires knowledge of what is essential, what is an add-on and which of all these requirements/options can be successfully implemented in the allotted period of time. The importance of this stage cannot be stressed enough; if the vision/goal cannot be articulated in a manner that all can understand, the knowledge tap will be opened to become the money drain. Different departments may compete for the same financial resources; management may be jockeying for their day in the sun; consulting corporations, eager to win the bid, may exaggerate their level of competency. These types of endeavors require those special skills of an individual or a team of very competent members to be/have a software architect, subject matter expert and business analyst.

Once the decision has been made and the application development stages have been defined, the next step is to determine which software development tools to employ. For the sake of this article, we will assume that the team has chosen an object oriented language such as Java and a variety of J EE components, a relationsional database and a vendor specific BRMS such as Blaze Advisor. Now, onto the point of this article.

Python programming language is general purpose open source programming language. One of its main features is flexibility and ease of use. Python has a variety of useful set of utilities and libraries for data processing and analytical tasks. Currently due to the rise in demand of big data processing python has grown in popularity because its features are easy to use which are core to the processing of huge chunks of information.

Guido Van Rossum, the pioneer of python, introduced python in the year 1980 and then implemented it in 1989. The intention behind the development of python was to make it open source language that can also be used for commercial projects. The fundamental principle of python is to write the code that is easy to use, highly readable and embrace writing fewer lines of code for achieving a particular task. One of the most popular standard libraries which have ready to use tools for performing a various work is Python Package Index. It was introduced in January 2016 and contains more than 72,000 packages for third-party software usage.

Python plays a critical role in linking data to customers. Recently python has found few entry barriers and many people have had access to have experienced the power of python in the past. So, what makes python the best language for big data analytics?

One of the reasons to choose python is that python ecosystem is very vibrant, the ratings at Redmonk are a proof of the strength python community. The Redmonk ranking is based on StackOverflow discussions and contribution made in Github to determine the popularity of programming language on the method used by users to ask questions about Python and the number of the open source projects contributions.

Tech Life in Michigan

Home of the Ford Motor Company and many other Fortune 500 and Fortune 1000 Companies, Michigan has a list of famous people that have made their mark on society. Famous Michiganians: Francis Ford Coppola film director; Henry Ford industrialist, Earvin Magic Johnson basketball player; Charles A. Lindbergh aviator; Madonna singer; Stevie Wonder singer; John T. Parsons inventor and William R. Hewlett inventor.
The expert knows more and more about less and less until he knows everything about nothing. Mahatma Gandhi
other Learning Options
Software developers near Dearborn Heights have ample opportunities to meet like minded techie individuals, collaborate and expend their career choices by participating in Meet-Up Groups. The following is a list of Technology Groups in the area.
Fortune 500 and 1000 companies in Michigan that offer opportunities for Oracle, MySQL, Cassandra, Hadoop Database developers
Company Name City Industry Secondary Industry
Lear Corporation Southfield Manufacturing Automobiles, Boats and Motor Vehicles
TRW Automotive Holdings Corp. Livonia Manufacturing Automobiles, Boats and Motor Vehicles
Spartan Stores, Inc. Byron Center Retail Grocery and Specialty Food Stores
Steelcase Inc. Grand Rapids Manufacturing Furniture Manufacturing
Valassis Communications, Inc. Livonia Business Services Advertising, Marketing and PR
Autoliv, Inc. Auburn Hills Manufacturing Automobiles, Boats and Motor Vehicles
Cooper-Standard Automotive Group Novi Manufacturing Automobiles, Boats and Motor Vehicles
Penske Automotive Group, Inc. Bloomfield Hills Retail Automobile Dealers
Con-Way Inc. Ann Arbor Transportation and Storage Freight Hauling (Rail and Truck)
Meritor, Inc. Troy Manufacturing Automobiles, Boats and Motor Vehicles
Visteon Corporation Van Buren Twp Manufacturing Automobiles, Boats and Motor Vehicles
Affinia Group, Inc. Ann Arbor Manufacturing Automobiles, Boats and Motor Vehicles
Perrigo Company Allegan Healthcare, Pharmaceuticals and Biotech Pharmaceuticals
BorgWarner Inc. Auburn Hills Manufacturing Automobiles, Boats and Motor Vehicles
Auto-Owners Insurance Lansing Financial Services Insurance and Risk Management
DTE Energy Company Detroit Energy and Utilities Gas and Electric Utilities
Whirlpool Corporation Benton Harbor Manufacturing Tools, Hardware and Light Machinery
Herman Miller, Inc. Zeeland Manufacturing Furniture Manufacturing
Universal Forest Products Grand Rapids Manufacturing Furniture Manufacturing
Masco Corporation Inc. Taylor Manufacturing Concrete, Glass, and Building Materials
PULTEGROUP, INC. Bloomfield Hills Real Estate and Construction Real Estate & Construction Other
CMS Energy Corporation Jackson Energy and Utilities Energy and Utilities Other
Stryker Corporation Portage Healthcare, Pharmaceuticals and Biotech Medical Devices
General Motors Company (GM) Detroit Manufacturing Automobiles, Boats and Motor Vehicles
Kellogg Company Battle Creek Manufacturing Food and Dairy Product Manufacturing and Packaging
The Dow Chemical Company Midland Manufacturing Chemicals and Petrochemicals
Kelly Services, Inc. Troy Business Services HR and Recruiting Services
Ford Motor Company Dearborn Manufacturing Automobiles, Boats and Motor Vehicles

training details locations, tags and why hsg

A successful career as a software developer or other IT professional requires a solid understanding of software development processes, design patterns, enterprise application architectures, web services, security, networking and much more. The progression from novice to expert can be a daunting endeavor; this is especially true when traversing the learning curve without expert guidance. A common experience is that too much time and money is wasted on a career plan or application due to misinformation.

The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:

  • Learn from the experts.
    1. We have provided software development and other IT related training to many major corporations in Michigan since 2002.
    2. Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
  • Discover tips and tricks about Oracle, MySQL, Cassandra, Hadoop Database programming
  • Get your questions answered by easy to follow, organized Oracle, MySQL, Cassandra, Hadoop Database experts
  • Get up to speed with vital Oracle, MySQL, Cassandra, Hadoop Database programming tools
  • Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
  • Prepare to hit the ground running for a new job or a new position
  • See the big picture and have the instructor fill in the gaps
  • We teach with sophisticated learning tools and provide excellent supporting course material
  • Books and course material are provided in advance
  • Get a book of your choice from the HSG Store as a gift from us when you register for a class
  • Gain a lot of practical skills in a short amount of time
  • We teach what we know…software
  • We care…
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