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Wednesday, 9 April 2014

Embracing SQL-MR to Handle Advanced (Analytical) Queries

The story behind the development of the SQL-mr function, as far as the world of enterprise data warehouse is concerned, is quite a funny one. Simply told, this resourceful function actually started out just as a simple expression evaluator, which is add, multiply, subtract and divide. It is from this humble beginning that this function grew into a full fledged programming language. With so much programming in the world, it is not impossible to wonder whether there aren’t enough of them yet. What is more, one cannot help but wonder what makes a new programming language more special than the earlier ones. Well, there are obviously convincing responses to your questions. 

This programming language usually runs in and as a SQL-mr function. The user passes on the program he or she wishes to run at the command line and done, it executes the code. Specifically, reading in normally record from the functions ON clause and passing then records back to your database. If you were already wondering if it can handle multi functions, then the answer is yes. What is more, it usually supports JDBC. This means that you can read from through a cursor variable, you can update, delete, insert records and even execute arbitrary SQL using a JDBC connection.

Another great thing about this function is that it bears the capacity to execute programs that were previously stored as enterprise data warehouse via the install command. This explains why it is considered an effectively kept procedure language.

There is actually a lot more of good things as far as this function is considered. Typically, SQL map reduce is a solution specifically designed for handling advanced analytical queries. Generally, the presence of more complex queries and increased data demands a more powerful enterprise data warehouse platform. A good number of database vendors have actually implemented SQL MapReduce. Better explained, it is a combination of the popular database language, SQL and a programming model developed by Google known as MapReduce.

Advantages of SQL MapReduce

  • Map reduce is usually implemented as a set of SQL table of functions. Despite being extremely sophisticated on the inside, these tables resemble the ones supported by SQL.
  • Individuals developing a report have to learn neither a new language nor a new set of statements. In any case, they just have to study the specific parameters of the MR functions.
  • Any existing reporting as well as an analytical tool that usually supports SQL can work effectively with SQL MapReduce.
  • SQL MapReduce is as storage independent and declarative as the SQL
  • With SQL MapReduce, developers have the liberty of writing their personal analytical functions and can use the language they consider comfortable to them.

Tuesday, 4 February 2014

Importance of Hadoop Training and Certification for Students


Before considering the importance and relevance of Hadoop Training and Certification for students, it is important and necessary to consider what constitutes Hadoop, its architecture, benefits and mode of operational usage for the benefit of users.

Hadood- an open sourced library with many benefits:

Essentially, as the scope of this paper would permit, Hadoop is an open sourced library which is readily available and downloadable from Apache Software Foundation.

One of the principal business advantages of Hadoop is that it provides for very convenient and easy distribution of data sets, possibly in petabytes, not over a single computer but over large clusters, or bunches of computers. Not only does it offer operational effectiveness but also increases performance of individual computers, while also shortening vital processing time. Besides, should any issues arise in individual computers, the other members of the cluster would be assigned to take over the tasks and duties of that affected computer, thereby reducing processing losses and time. This beneficially moves the company as a whole and helps increase performance, productivity and profitability in the medium and long term. However, the only concern that this author points out is in terms of large scale investments and operational costs that are necessary to enforce and sustain large clusters of computers, but this does even out in the long run through reduction of losses and increased productivity and optimally gains the benefits of economies of large scale in software libraries. 

Essentially this works on the architectural principle of one Master Computer, one second- in- command Back up Computer and a number of Slave computers, depending upon needs and operational viability.

Hadood architecture:

The Master computer issues orders that are processed by Slave computers and in the absence of Master Computer the Backup Computer takes over the tasks, responsibilities and practices of the Master Computer with equal apparent ease, efficacy and benefit to both user and enforcer.

Hadoop Training and certification is very important, since this one library which holds tremendous scope for a very good future, considering that businesses are now leap frogging from MB and GB to possible PB (petabytes) in future. With great increases in business development and increased activities, current and contemporary computer systems are unable to cope with increased inputs and thus there is greater need and demand for software that could perform massive computing tasks at high speed and low processing times. Besides, many major blue chip companies have not taken this library into their fold and are reaping rich dividends over time. In addition, this library is most innovative and is amenable for reform measures in future too, to keep pace and speed with changing, dynamic and perhaps overwhelming technology too.

Future of Hadood in evolving and ever changing software world:

In short, keeping in view the future needs, aspirations and demands of future technology and their impact on education and enlightenment, the Hadoop Training and Certification would be the best thing that has ever happened to many aspirant software professionals, developers and consultants over time. Since this is an open source and innovative library, it does not depend upon often-failing-servers, but itself takes up the responsibility of detecting and remedying failures at application stages, thus ensuring optimum and maximum protection, sustenance, propagation and perpetration of knowledge , exposure and skill development in the domains of software development, consultancy services and training that could go on a long, long way into the future, undeterred and unfazed by newer technological upgradations and introduction of newer software into this domains.

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Monday, 13 January 2014

Advanced Analytics Platforms Improve Business Productivity

Business is one of the best places to see the law ‘survival of the fittest’ in operation. Companies that fail to evolve over time are rendered obsolete, and they end up losing their market share to companies which do keep up with changing times. It has, therefore, become necessary for companies to ensure that they get the best possible feedback on their operations and then act on it quickly and efficiently. Since evolving business practice, products, and services has become a continuous need for the modern business, companies have had to seek better solutions to address the challenge. This is why advanced analytic platform has been deemed as an important solution for the modern business. 

These platforms collect data from operations both internally and externally for the business. They then store this information in data management systems to make it possible for the data to be processed and analyzed. The data is processed to ensure that it is optimal for use in business analytics. Once the data has been optimized, it can then be analyzed to derive useful insights that allow the business to evolve and streamline both its operations and product offerings to the consumer market. Here is how these platforms are able to improve business productivity for companies that are using these solutions. 

Internal streamlining 

As companies grow larger over time, it becomes increasingly difficult to maintain efficiency in their operations. This is because the larger the company, the greater the amount of bureaucracy with which the company is saddled. This creates a number of bottlenecks that may interfere with productivity and reduce the company’s output. Advanced analytic platform solutions deployed within a business environment can assist the company to streamline its internal operations. The system provides insight on business processes that can be optimized as well as areas where bureaucracy can be eliminated for increased efficiency. 

External evolution 

The market is constantly changing and companies that are not seen as evolving with the market eventually get phased out of the market. Business analytics makes it possible for companies to keep up with the changing market. These insights allow the business to create a strategy that allows for reorientation to meet changing consumer sentiments and preferences. Companies are, therefore, able to ensure that they are dynamic. There are companies which have been able to create new products and services to meet new consumer demands. Businesses are expected to continue seeing a positive impact of investing in analytical tools. 

Thursday, 28 November 2013

How Companies Should Go About the Process of Integrating Big Data Analytics into Their Operations

Big Data Analytics

Analytics big data is the way companies are integrating information technology into their operations at a core level. This is the use of specialized information technology systems to derive useful information from the data that they have accumulated in their operations. However, the recent nature of analytics with a big data business context is a recent innovation. As a result, so many companies are unsure as to how they should go about the integration process so as to get the most value out of the system. Here are the recommended stages through which a company should integrate analytics big data into its operations.

Initial stage

The initial stage is important as it allows the company to get a realistic view of the kind of data that they will be expected to deal with in the implementation of analytics. The IT department must get as much information as they can on the kind of data and data quantities with which they need to prepare to deal.

Storage stage

Big data means a need for big storage. As a result, the next stage is companies have to look for storage solutions for their big data. This means that they have to invest in data warehouses that are capable of handling their data needs. It is important to note that the quality of the data warehouse will have an impact on their foray into analytics big data. The better the warehouse, the easier it will be to build a powerful data analytics solution into their system.

Past analytics to predictive analytics stage

The next stage of analytics big data is moving from past analytics to predictive analytics. The analytics platform that they are integrating into their operations will only be able to provide information on what happened in the past. This is intelligence that is based on a historical analysis of data records. As the system is improved, presentation of data is automated with the introduction of executive dashboards. These executive dashboards are used to provide reports as they are requested. At this stage, the IT department is then able to integrate predictive tools into their data management system. These use algorithms and mathematical models to make it possible to process current data into useful insights on future trends.

Real-time usage

The last stage is where analytics big data has been implemented into everyday operations. Information is processed as it is acquired and insights implemented as they are derived.