Over time, companies are migrating from COBOL to the latest standard of C# solutions due to reasons such as cumbersome deployment processes, scarcity of trained developers, platform dependencies, increasing maintenance fees. Whether a company wants to migrate to reporting applications, operational infrastructure, or management support systems, shifting from COBOL to C# solutions can be time-consuming and highly risky, expensive, and complicated. However, the following four techniques can help companies reduce the complexity and risk around their modernization efforts. 

All COBOL to C# Solutions are Equal 

It can be daunting for a company to sift through a set of sophisticated services and tools on the market to boost their modernization efforts. Manual modernization solutions often turn into an endless nightmare while the automated ones are saturated with solutions that generate codes that are impossible to maintain and extend once the migration is over. However, your IT department can still work with tools and services and create code that is easier to manage if it wants to capitalize on technologies such as DevOps. 

Narrow the Focus 

Most legacy systems are incompatible with newer systems. For years now, companies have passed legacy systems to one another without considering functional relationships and proper documentation features. However, a detailed analysis of databases and legacy systems can be useful in decision-making and risk mitigation in any modernization effort. It is fairly common for companies to uncover a lot of unused and dead code when they analyze their legacy inventory carefully. Those discoveries, however can help reduce the cost involved in project implementation and the scope of COBOL to C# modernization. Research has revealed that legacy inventory analysis can result in a 40% reduction of modernization risk. Besides making the modernization effort less complex, trimming unused and dead codes and cost reduction, companies can gain a lot more from analyzing these systems. 

Understand Thyself 

For most companies, the legacy system entails an entanglement of intertwined code developed by former employees who long ago left the organization. The developers could apply any standards and left behind little documentation, and this made it extremely risky for a company to migrate from a COBOL to C# solution. In 2013, CIOs teamed up with other IT stakeholders in the insurance industry in the U.S to conduct a study that found that only 18% of COBOL to C# modernization projects complete within the scheduled period. Further research revealed that poor legacy application understanding was the primary reason projects could not end as expected. 

Furthermore, using the accuracy of the legacy system for planning and poor understanding of the breadth of the influence of the company rules and policies within the legacy system are some of the risks associated with migrating from COBOL to C# solutions. The way an organization understands the source environment could also impact the ability to plan and implement a modernization project successfully. However, accurate, in-depth knowledge about the source environment can help reduce the chances of cost overrun since workers understand the internal operations in the migration project. That way, companies can understand how time and scope impact the efforts required to implement a plan successfully. 

Use of Sequential Files 

Companies often use sequential files as an intermediary when migrating from COBOL to C# solution to save data. Alternatively, sequential files can be used for report generation or communication with other programs. However, software mining doesn’t migrate these files to SQL tables; instead, it maintains them on file systems. Companies can use data generated on the COBOL system to continue to communicate with the rest of the system at no risk. Sequential files also facilitate a secure migration path to advanced standards such as MS Excel. 

Modern systems offer companies a range of portfolio analysis that allows for narrowing down their scope of legacy application migration. Organizations may also capitalize on it to shed light on migration rules hidden in the ancient legacy environment. COBOL to C# modernization solution uses an extensible and fully maintainable code base to develop functional equivalent target application. Migration from COBOL solution to C# applications involves language translation, analysis of all artifacts required for modernization, system acceptance testing, and database and data transfer. While it’s optional, companies could need improvements such as coding improvements, SOA integration, clean up, screen redesign, and cloud deployment.

One of the biggest challenges faced by senior IT professionals in organizations is the choice of the right software vendor. In the highly competitive enterprise software industry, there are lot of vendors who claim to offer the best software for the problem and it can be really daunting to narrow down the best choice. Additionally, enterprise software costs can often run into millions of dollars thereby leaving very little margin of error. The real cost of choosing a wrong software can often result into losses much more than the cost of the software itself as highlighted by software disasters experienced by leading companies like HP, Nike etc. In such a scenario, senior IT professionals despite years of expertise can find it very difficult to choose the right business software vendor for their organization.

Here are some of the proven ways of short-listing and selecting the right business software vendor for your organization,

·         Understand and Define The Exact Need First: Before embarking on a journey to select the software vendor, it is critical to understand and define the exact problem you want the software to solve. The paramount question to be asked is what business objective does the software need to solve. Is the software required to “reduce costs” or is it to “improve productivity”? Extracting and defining this fundamental question is the bare minimum but necessary step to go searching for the right vendor. It will then form the basis of comparing multiple vendors on this very need that your organization has and will help drive the selection process going forward. The detailed approach involves creating a set of parameters that the software needs to meet in order to be considered. In fact, consider categorizing these parameters further in “must-haves”, “good to have” etc. which will help you assign relevant weights to these parameter and how the software’s fare on each of these parameters

·         Building The List of Vendors Who Meet The Need: Once you have defined your need and distilled that need into various parameters, it’s time to built the list of vendors who you think will meet the need. This is akin to a lead generation model wherein you want to identify a large enough pool and then filters your list down to the best ones. There are multiple ways of building a list of vendors and more often than not, you must use a combination of these methods to build a good enough list.

o   Use Industry Reports: We discussed the IT intelligence offered by leading industry firms Gartner and Forrester in How To Keep On Top Of Latest Trends In Information Technology. These firms based on their access to leading software vendors and CIO network publish vendor comparison research reports across specific verticals as well as specific technologies. Gartner’s Magic Quadrant and Forrester’s Wave are a very good starting point to get an insight into the best software vendors. For example, if you were looking for a CRM solution, you could look for Gartner’s Magic Quadrant for CRM and look at the vendors that make the list. These reports can be pricey but well worth the money if you are going to invest hundreds of thousands in the software. Having said that, you don’t have to trust these report blindly because how these firms define the best software may not match how you define the best software for your organization

o   Competitive Intelligence: If you are a smart professional, you are already keeping tabs of your competition. Chances are that if you are a big organization, you might see a Press Release either from your competitor or their vendor announcing the implementation of new software. Extrapolate that across 5-10 key competitors of yours and you might discover the vendors that your competitors are choosing. This gives you a good indicator that the vendors used by your competitors must be offering something right.

F# is excellent for specialties such as scientific computing and data analysis. It is an excellent choice for enterprise development as well. There are a few great reasons why you should consider using F# for your next project.

Concise

F# is not cluttered up with coding noise;  no pesky semicolons, curly brackets, and so on. You almost never have to specify the kind of object you're referencing because of its powerful type inference system. It usually takes fewer lines of code to solve the same issue.

Convenient

Common programming tasks are much easier in F#. These include generating and using state machines, comparison and equality, list processing, as well as complex type definitions. It is very easy to generate powerful and reusable code because functions are first class objects. This is done by creating functions that have other functions as parameters or that combine existing functions to generate a new functionality.

Correctness

F# has a strong type system, and, therefore, prevents many common errors such as null reference exceptions. Valuables are immutable by default which, too, prevents a huge class of errors. You can also encode business logic by utilizing the type system. When done correctly, it is impossible to mix up units of measure or to write incorrect code thereby decresing the need of unit tests.

Concurrency

F# has number of built-in libraries. These libraries help when more than one thing at a time is occurring. Parallelism and asynchronous programming are very simple. There is also a built-in actor model as well as excellent support for event handling and functional reactive programming. Sharing state and avoiding locks are much easier because data structures are immutable by default.

Completeness

F# also supports other styles that are not 100 percent pure. This makes it easier to interact with the non-pure world of databases, websites, other applications, and so on. It is actually designed as a hybrid functional/OO language. F# is also part of the .NET ecosystem. This gives you seamless access to all the third party .NET tools and libraries. It operates on most platforms. These platforms include Linux and smartphones via mono. Visual Studio is integrates with F# as well. This means you get many plug-ins for unit tests, a debugger, a IDE with IntelliSense support, other development tasks. You can use MonoDevelop IDE on Linux.

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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/

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