C Programming Training Classes in Lancaster, California
Learn C Programming in Lancaster, California 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 C Programming related training offerings in Lancaster, California: C Programming Training
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Blog Entries publications that: entertain, make you think, offer insight
Memory management is always a priority in pretty much any programming language you would want to use. In the lower level languages such as C, there are a number of functions which help you manage the memory your application uses, but they are not the easiest to use. Some of the more modern programming languages such as Python, Ruby, Perl, and of course the subject of this article, Javascript all have a built in feature called garbage collection.
Garbage collection essentially means that the languages compiler will automatically free the memory being occupied by unused variables and objects, but there is no telling when this could occur. It is purely down to the compiler to decide when the garbage collection process should be initiated.
Big data is now in an incredibly important part of how many major businesses function. Data analysis, or the finding of facts from large volumes of data, helps businesses make many of their important decisions. Companies that conduct business on a national or international scale rely on big data in order to plot the general direction of their business. The concept of big data can be very confusing due to the sheer scale of information involved. By following a few simple guidelines, even the layman can understand big data and its impacts on everyday life.
What Exactly is Big Data?
Just about everyone can understand the concept of data. Data is information, and information is everywhere in the modern world. Anytime you use any piece of technology you are making use of data. Anytime you read a book, skim the newspaper or listen to music you are also making use of data. Your brain interprets and organizes data constantly from your senses and your thoughts.
Big data, much like its name infers, simply describes this same data on a large sale. The internet allowed the streaming, sharing and collecting of data on a scale never before imaginable and storage technology has allowed ever increasing hoards of data to be accumulated. In order for something to be considered “big data” it must be at least 10 terabytes or more of information. To put that in perspective, consider that 10 terabytes represents the entire printed collection of material in the Library of Congress. What’s even more remarkable is that many businesses work with far more than the minimum 10 terabytes of data. UPS stores over 16 petabytes of data about its packages and customers. That’s 16,000 terabytes or the equivalent to 1,600 printed libraries of congress. The sheer amount of that data is nearly impossible for a human to comprehend, and analysis of this data is only possible with computers.
How do Big Data Companies Emerge?
All of this information comes from everywhere on the internet. The majority of the useful data includes customer information, search engine logs, and entries on social media networks to name a few. This data is constantly generated by the internet at insane rates. Specified computers and software programs are created and operated by big data companies that collect and sort this information. These programs and hardware are so sophisticated and so specialized that entire companies can be dedicated to analyzing this data and then selling it to other companies. The raw data is distilled down into manageable reports that company executives can make use of when handling business decisions.
The Top Five:
These are the five biggest companies, according to Forbes, in the business of selling either raw data reports or analytics programs that help companies to compile their own reports.
1. Splunk
Splunk is currently valued at $186 million. It is essentially a program service that allows companies to turn their own raw data collections into usable information.
2. Opera Solutions
Opera Solutions is valued at $118 million. It serves as a data science service that helps other companies to manage the raw data that pertains to them. They can offer either direct consultation or cloud-based service.
3. Mu Sigma
Mu Sigma is valued at $114 million. It is a slightly smaller version of Opera Solutions, offering essentially the same types of services.
4. Palantir
Palantir is valued at $78 million. It offers data analysis software to companies so they can manage their own raw data analysis.
5. Cloudera
Cloudera is valued at $61 million. It offers services, software and training specifically related to the Apahce Hadoop-based programs.
The software and services provided by these companies impact nearly all major businesses, industries and products. They impact what business offer, where they offer them and how they advertise them to consumers. Every advertisement, new store opening or creation of a new product is at least somewhat related to big data analysis. It is the directional force of modern business.
Sources:
http://www.sas.com/en_us/insights/big-data/what-is-big-data.html
http://www.forbes.com/sites/gilpress/2013/02/22/top-ten-big-data-pure-plays/
http://www.whatsabyte.com/
Related:
Top Innovative Open Source Projects Making Waves in The Technology World
Is the U.S. the Leading Software Development Country?
How to Keep On Top Of the Latest Trends in Information Technology
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.
Learning SQL development can seem like an overwhelming task at first. However, mastering just a few key points will help ease your way through 80 percent of the day-to-day challenges when writing stored procedures and solving common problems. Here are three important SQL development factors to keep in mind:
Outer Joins
One of the most crucial things to understand in SQL server are joins. Joins are a way to retrieve data from two or more tables based on logical relationships between them. Joins dictate how Microsoft SQL Server ought to use data from one table to select the rows in another table.
In my experience inner joins are intuitive while outer joins can present additional hours of grief by overlooking associations in the other table(s). The outer join is the key to answering questions about what the database does not have. For example, if you need to make a query to display all the students who are without report-cards, you’ll need a left join to get all students coupled with a “where clause” to return the ones who have nulls for their report card table columns in the results.
Many talented Java script programmers have muddled through the SQL Server by deficient coding around the inner join. As a result, their queries can take five hours to run, whereas, properly written left joins, can take only two seconds to run.
Aggregation
Grouping results comes up in SQL a lot more than you might think. Knowing how to write a query when answering questions such as, “What’s the average grade for each teacher’s student list?” is invaluable. This kind of question cannot be answered with a single table or solely by joins. You’ll often find you need to use joins in conjunction with group by statements. Always write the raw query first and then look at the results. Next, you have to figure out the best way to group them, rewrite your select clause and add a group by clause in the end.
Digging Through Data
I find this is the most lacking skill in many programmers. In fact, many otherwise-talented programmers holding Master’s Degrees fail to get jobs because they couldn’t analyze rows of data objectively during interviews. It’s just something that’s not taught but is crucial to get under you belt. Why? Eventually, some query is not going to perform as you may expect. And, the only way to find discrepancies is to look at rows of data, identify what join isn’t finding a match or where bad data is throwing things into chaos. Get familiar with how joins actually work, even if you have to manually walk through the logic of a large stored procedure’s tree of joins. It’s boring and time-consuming but absolutely necessary.
Take the time to master the core skills that will make you a successful SQL Programmer and avoid queries that run for five hours!
Tech Life in California
| Company Name | City | Industry | Secondary Industry |
|---|---|---|---|
| Mattel, Inc. | El Segundo | Retail | Sporting Goods, Hobby, Book, and Music Stores |
| Spectrum Group International, Inc. | Irvine | Retail | Retail Other |
| Chevron Corp | San Ramon | Energy and Utilities | Gasoline and Oil Refineries |
| Jacobs Engineering Group, Inc. | Pasadena | Real Estate and Construction | Construction and Remodeling |
| eBay Inc. | San Jose | Software and Internet | E-commerce and Internet Businesses |
| Broadcom Corporation | Irvine | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Franklin Templeton Investments | San Mateo | Financial Services | Investment Banking and Venture Capital |
| Pacific Life Insurance Company | Newport Beach | Financial Services | Insurance and Risk Management |
| Tutor Perini Corporation | Sylmar | Real Estate and Construction | Construction and Remodeling |
| SYNNEX Corporation | Fremont | Software and Internet | Data Analytics, Management and Storage |
| Core-Mark International Inc | South San Francisco | Manufacturing | Food and Dairy Product Manufacturing and Packaging |
| Occidental Petroleum Corporation | Los Angeles | Manufacturing | Chemicals and Petrochemicals |
| Yahoo!, Inc. | Sunnyvale | Software and Internet | Software and Internet Other |
| Edison International | Rosemead | Energy and Utilities | Gas and Electric Utilities |
| Ingram Micro, Inc. | Santa Ana | Computers and Electronics | Consumer Electronics, Parts and Repair |
| Safeway, Inc. | Pleasanton | Retail | Grocery and Specialty Food Stores |
| Gilead Sciences, Inc. | San Mateo | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
| AECOM Technology Corporation | Los Angeles | Real Estate and Construction | Architecture,Engineering and Design |
| Reliance Steel and Aluminum | Los Angeles | Manufacturing | Metals Manufacturing |
| Live Nation, Inc. | Beverly Hills | Media and Entertainment | Performing Arts |
| Advanced Micro Devices, Inc. | Sunnyvale | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Pacific Gas and Electric Corp | San Francisco | Energy and Utilities | Gas and Electric Utilities |
| Electronic Arts Inc. | Redwood City | Software and Internet | Games and Gaming |
| Oracle Corporation | Redwood City | Software and Internet | Software and Internet Other |
| Symantec Corporation | Mountain View | Software and Internet | Data Analytics, Management and Storage |
| Dole Food Company, Inc. | Thousand Oaks | Manufacturing | Food and Dairy Product Manufacturing and Packaging |
| CBRE Group, Inc. | Los Angeles | Real Estate and Construction | Real Estate Investment and Development |
| First American Financial Corporation | Santa Ana | Financial Services | Financial Services Other |
| The Gap, Inc. | San Francisco | Retail | Clothing and Shoes Stores |
| Ross Stores, Inc. | Pleasanton | Retail | Clothing and Shoes Stores |
| Qualcomm Incorporated | San Diego | Telecommunications | Wireless and Mobile |
| Charles Schwab Corporation | San Francisco | Financial Services | Securities Agents and Brokers |
| Sempra Energy | San Diego | Energy and Utilities | Gas and Electric Utilities |
| Western Digital Corporation | Irvine | Computers and Electronics | Consumer Electronics, Parts and Repair |
| Health Net, Inc. | Woodland Hills | Healthcare, Pharmaceuticals and Biotech | Healthcare, Pharmaceuticals, and Biotech Other |
| Allergan, Inc. | Irvine | Healthcare, Pharmaceuticals and Biotech | Biotechnology |
| The Walt Disney Company | Burbank | Media and Entertainment | Motion Picture and Recording Producers |
| Hewlett-Packard Company | Palo Alto | Computers and Electronics | Consumer Electronics, Parts and Repair |
| URS Corporation | San Francisco | Real Estate and Construction | Architecture,Engineering and Design |
| Cisco Systems, Inc. | San Jose | Computers and Electronics | Networking Equipment and Systems |
| Wells Fargo and Company | San Francisco | Financial Services | Banks |
| Intel Corporation | Santa Clara | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Applied Materials, Inc. | Santa Clara | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Sanmina Corporation | San Jose | Computers and Electronics | Semiconductor and Microchip Manufacturing |
| Agilent Technologies, Inc. | Santa Clara | Telecommunications | Telecommunications Equipment and Accessories |
| Avery Dennison Corporation | Pasadena | Manufacturing | Paper and Paper Products |
| The Clorox Company | Oakland | Manufacturing | Chemicals and Petrochemicals |
| Apple Inc. | Cupertino | Computers and Electronics | Consumer Electronics, Parts and Repair |
| Amgen Inc | Thousand Oaks | Healthcare, Pharmaceuticals and Biotech | Biotechnology |
| McKesson Corporation | San Francisco | Healthcare, Pharmaceuticals and Biotech | Pharmaceuticals |
| DIRECTV | El Segundo | Telecommunications | Cable Television Providers |
| Visa, Inc. | San Mateo | Financial Services | Credit Cards and Related Services |
| Google, Inc. | Mountain View | Software and Internet | E-commerce and Internet Businesses |
training details locations, tags and why hsg
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.
- We have provided software development and other IT related training to many major corporations in California since 2002.
- 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 C Programming programming
- Get your questions answered by easy to follow, organized C Programming experts
- Get up to speed with vital C Programming 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…
Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.
