Crystal Reports Training Classes in Columbia, South Carolina

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Machine learning systems are equipped with artificial intelligence engines that provide these systems with the capability of learning by themselves without having to write programs to do so. They adjust and change programs as a result of being exposed to big data sets. The process of doing so is similar to the data mining concept where the data set is searched for patterns. The difference is in how those patterns are used. Data mining's purpose is to enhance human comprehension and understanding. Machine learning's algorithms purpose is to adjust some program's action without human supervision, learning from past searches and also continuously forward as it's exposed to new data.

The News Feed service in Facebook is an example, automatically personalizing a user's feed from his interaction with his or her friend's posts. The "machine" uses statistical and predictive analysis that identify interaction patterns (skipped, like, read, comment) and uses the results to adjust the News Feed output continuously without human intervention. 

Impact on Existing and Emerging Markets

The NBA is using machine analytics created by a California-based startup to create predictive models that allow coaches to better discern a player's ability. Fed with many seasons of data, the machine can make predictions of a player's abilities. Players can have good days and bad days, get sick or lose motivation, but over time a good player will be good and a bad player can be spotted. By examining big data sets of individual performance over many seasons, the machine develops predictive models that feed into the coach’s decision-making process when faced with certain teams or particular situations. 

General Electric, who has been around for 119 years is spending millions of dollars in artificial intelligence learning systems. Its many years of data from oil exploration and jet engine research is being fed to an IBM-developed system to reduce maintenance costs, optimize performance and anticipate breakdowns.

Over a dozen banks in Europe replaced their human-based statistical modeling processes with machines. The new engines create recommendations for low-profit customers such as retail clients, small and medium-sized companies. The lower-cost, faster results approach allows the bank to create micro-target models for forecasting service cancellations and loan defaults and then how to act under those potential situations. As a result of these new models and inputs into decision making some banks have experienced new product sales increases of 10 percent, lower capital expenses and increased collections by 20 percent. 

Emerging markets and industries

By now we have seen how cell phones and emerging and developing economies go together. This relationship has generated big data sets that hold information about behaviors and mobility patterns. Machine learning examines and analyzes the data to extract information in usage patterns for these new and little understood emergent economies. Both private and public policymakers can use this information to assess technology-based programs proposed by public officials and technology companies can use it to focus on developing personalized services and investment decisions.

Machine learning service providers targeting emerging economies in this example focus on evaluating demographic and socio-economic indicators and its impact on the way people use mobile technologies. The socioeconomic status of an individual or a population can be used to understand its access and expectations on education, housing, health and vital utilities such as water and electricity. Predictive models can then be created around customer's purchasing power and marketing campaigns created to offer new products. Instead of relying exclusively on phone interviews, focus groups or other kinds of person-to-person interactions, auto-learning algorithms can also be applied to the huge amounts of data collected by other entities such as Google and Facebook.

A warning

Traditional industries trying to profit from emerging markets will see a slowdown unless they adapt to new competitive forces unleashed in part by new technologies such as artificial intelligence that offer unprecedented capabilities at a lower entry and support cost than before. But small high-tech based companies are introducing new flexible, adaptable business models more suitable to new high-risk markets. Digital platforms rely on algorithms to host at a low cost and with quality services thousands of small and mid-size enterprises in countries such as China, India, Central America and Asia. These collaborations based on new technologies and tools gives the emerging market enterprises the reach and resources needed to challenge traditional business model companies.

When making a strategic cloud decision, organizations can follow either one of two ideologies: open or closed.

In the past, major software technologies have been widely accepted because an emerging market leader simplified the initial adoption.  After a technology comes of age, the industry spawns open alternatives that provide choice and flexibility, and the result is an open alternative that quickly gains traction and most often outstrips the capabilities of its proprietary predecessor.

After an organization invests significantly in a technology, the complexity and effort required steering a given workload onto a new system or platform is, in most cases, significant. Switching outlays, shifting to updated or new software/hardware platforms, and the accompanying risks may lead to the ubiquitousness of large, monolithic and complex ERP systems – reason not being that they offer the best value for an organization, but rather because shifting to anything else is simply – unthinkable.

There’s no denying that these are critical considerations today since a substantial number of organizations are making their first jump into the cloud and making preparations for the upsetting shift in how IT is delivered to both internal and external clientele. Early adopters are aware of the fact that the innovation brought about by open technologies can bring dramatic change, and hence are realizing how crucial it is to be able to chart their own destiny.

 
 
Python is a powerful tool that can be used for many automation tasks in the workplace. It’s notorious for being one of the most simple and versatile options available in the world of programming languages. For this reason, many people choose to automate an enormous amount of their workflow with Python. We’ve compiled a few ideas for automating the boring stuff using Python. Let’s take a look.
 
Managing Emails
 
Most businesses rely on emails being sent out regularly in order to ensure everything runs smoothly. Doing this by hand can be boring and time-consuming. To alleviate this, there are packages written with and for Python that enable you to automate certain aspects of this process. Adding and removing individuals from mailing lists can be automated as well, especially if your business has a policy to automatically add and remove people from certain mailing lists when certain conditions are met. For example, after a customer of yours doesn’t interact with your company after an extended period of time, it may be prudent to remove them from your mailing list, or you can send them a premade email reminding them of your services. This is just one way that you can save your company time and money using automation with Python.
 
Repetitive File System Operations
 
Even for personal tasks, Python excels at performing repetitive file system operations. For example, it can convert files, rename, move, delete, and sort files as much as you need it to. This can be useful in many ways. If you have a folder of mp3 files that you need to compress, this can be sped up using Python. Additionally, you can create a set of criteria that need to be met in order for a given file to be considered useless, and then delete it. As a side note, be extremely careful when automating any sort of file deletion or altering, because a bug in your program can cause severe damage to your data and even to your computer. Still, these tools are extremely powerful and can be life-saving when used properly. 
 
Start-up Tasks
 
Whether you’re running a server or just using your own personal computer, there are always tasks that need to be done when your computer starts up, or you’re beginning a certain process. For example, you can automate the task of backing up your email inbox. This can ensure your files are being kept safe, and it can be triggered whenever your start up your computer. Additionally, if you need to collect or create any sort of logging data in order to document daily operations, you can use Python to alleviate some of these time-consuming processes. 
 
Web Scraping
 
And finally, we have Web Scraping. This process may be slightly more advanced for a beginner Python user, but it doesn’t take a terribly long time to learn, and it opens up a whole new world of opportunity in terms of data collection and management. Web scraping is extremely important because it not only allows you to automatically search for certain pieces of content on the internet, but it can also alert you to changes and updates to existing websites. If your business relies on certain trends on social media, you can scrape sites while searching for the presence of certain keywords, and if you’re a stock trader or bitcoin guru, you can automate some of your price-checking and set custom alerts for price changes. The field of web scraping is enormous, and there is a practically infinite amount of content written on this particular subject. If you’re interested in learning more, there are vast amounts of free resources on the internet that can help you get started. Web scraping is certainly one of the most important skills to have in almost any line of work.
 
Get Creative!
 
At this point, we’d like to advise you to get more familiar with the libraries and APIs that are available to you. Each individual workflow is different and requires familiarity with different technologies. Because of this, you will know better than anybody else which items are worth automating and which aren’t. Some people try to automate everything, and some people prefer to do certain tasks manually, but sometimes spending a few hours automating a job that takes one minute will end up being a time-saver after only a few months.
 
We’ve gone over quite a few options in this article, but no single human alive is familiar with absolutely everything Python can do. Hopefully, you’re now more familiar with the options available to you, and you should now be better equipped to search for further information that is more relevant to your specific use case. Have fun digging into the many nuances and functionalities that the Python language has to offer!

In programming, memory leaks are a common issue, and it occurs when a computer uses memory but does not give it back to the operating system. Experienced programmers have the ability to diagnose a leak based on the symptoms. Some believe every undesired increase in memory usage is a memory leak, but this is not an accurate representation of a leak. Certain leaks only run for a short time and are virtually undetectable.

Memory Leak Consequences

Applications that suffer severe memory leaks will eventually exceed the memory resulting in a severe slowdown or a termination of the application.

How to Protect Code from Memory Leaks?

Preventing memory leaks in the first place is more convenient than trying to locate the leak later. To do this, you can use defensive programming techniques such as smart pointers for C++.  A smart pointer is safer than a raw pointer because it provides augmented behavior that raw pointers do not have. This includes garbage collection and checking for nulls.

If you are going to use a raw pointer, avoid operations that are dangerous for specific contexts. This means pointer arithmetic and pointer copying. Smart pointers use a reference count for the object being referred to. Once the reference count reaches zero, the excess goes into garbage collection. The most commonly used smart pointer is shared_ptr from the TR1 extensions of the C++ standard library.

Static Analysis

The second approach to memory leaks is referred to as static analysis and attempts to detect errors in your source-code. CodeSonar is one of the effective tools for detection. It provides checkers for the Power of Ten coding rules, and it is especially competent at procedural analysis. However, some might find it lagging for bigger code bases.

How to Handle a Memory Leak

For some memory leaks, the only solution is to read through the code to find and correct the error. Another one of the common approaches to C++ is to use RAII, which an acronym for Resource Acquisition Is Initialization. This approach means associating scoped objects using the acquired resources, which automatically releases the resources when the objects are no longer within scope. RAII has the advantage of knowing when objects exist and when they do not. This gives it a distinct advantage over garbage collection. Regardless, RAII is not always recommended because some situations require ordinary pointers to manage raw memory and increase performance. Use it with caution.

The Most Serious Leaks

Urgency of a leak depends on the situation, and where the leak has occurred in the operating system. Additionally, it becomes more urgent if the leak occurs where the memory is limited such as in embedded systems and portable devices.

To protect code from memory leaks, people have to stay vigilant and avoid codes that could result in a leak. Memory leaks continue until someone turns the system off, which makes the memory available again, but the slow process of a leak can eventually prejudice a machine that normally runs correctly.

 

Related:

The Five Principles of Performance

In Demand IT Skills

Tech Life in South Carolina

Motto: Animis Opibusque Parati / Dum Spiro Spero Prepared in mind and resources / While I breathe, I hope South Carolina is one of just three states that have not agreed to use competitive international math and language standards. The state has a diverse group of institutions of higher education, from large state-funded research universities to small colleges that cultivate liberal arts, religious or military tradition.
Life is a traveling to the edge of knowledge, then a leap taken. David Herbert Lawrence
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Software developers near Columbia 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 South Carolina that offer opportunities for Crystal Reports developers
Company Name City Industry Secondary Industry
Sonoco Products Co. Hartsville Manufacturing Paper and Paper Products
SCANA Corporation Cayce Energy and Utilities Gas and Electric Utilities
ScanSource, Inc. Greenville Computers and Electronics Consumer Electronics, Parts and Repair

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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 South Carolina 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 Crystal Reports programming
  • Get your questions answered by easy to follow, organized Crystal Reports experts
  • Get up to speed with vital Crystal Reports 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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