Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

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.

Related:

F# - Marching Towards Top 10 Programming Languages

What Are the Advantages of Python Over Ruby?

Top 10 Programming Languages Expected To Be In Demand in 2014

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.

A whole new world was thrown wide open with the advent of the concept of open source. The biggest advantage of open source projects is the easy availability of the source code and also the rights to tweak it or modify the code as we deem fit.

Listed below are some top open source projects that are making waves with their innovative ideas at this moment.

ProjectLibre

Project Libre is the open source replacement of Microsoft Project. It was one among the top 10 open source projects of 2013. With over 6 million downloads; it has most certainly captured the imagination of people around the world. Details of project Libre could be found at http://www.projectlibre.org/ . Project Libre has separate release for mainframes. It also has a web based version which further increases its overall appeal. One of the main advantages is that it has a list of tasks that can be tracked to closure. It can also be used in conjunction with LibreOffice to provide a great set of tools to the team leaders.

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