Emerging Technologies in Business Intelligence & Artificial Intelligence

Technology has left no industry or business without being considered or undergone Gap Analysis by their own team or from consultancies. Companies running on manual process still, are the one who are spending a lot on their operations whereas at other ends, companies utilizing technology as a solution are continuously growing with their revenue and operations with least efforts.

Need of BI and AI in current process;

Gone are those days, when regular meeting, analytics, and derivations, strategy formulations, meetings where used to take place followed up with investment of time in face to face meetings and report writing. Now technology and algorithms are robust enough that may take decisions by recalling and scanning through the old data, capability for delivering reports in real time environment is being given utmost importance now.

BI systems have the capability to influence decisions that would have strategic impact on enterprise.

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Take away notes;

– BI can help organizations making sense out of their huge collected data

– AI can help giving insights to the strategy and business plans by learning from past

– AI can help making super decisions before the process ends, so in between decisions and insights of the process would really help organizations to save efforts, costs and time before committing for a big failure.

It is highly suggested for industries and organizations to undergo gap analysis, there is always a better way to optimize the operations for achieving revenues and quality with technology.

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Growing technology with unaddressed questions and scenarios

Technology is growing and changing at such a fast pace, that today’s development and concepts get old by tomorrow!. Code’s or machine’s ability to learn and response without being programmed has become utmost popular and is leading most of the daily process, where least human involvement is required now.

Focusing on the trend of data being generated from ample of processes on day to day basis in organization has lead Machine learning to emphasize more on the development part where programs can be developed to deal with new strains of data from the various processes.

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The pace at which the data is being generated from a small process or a bigger process is in equal demand for auto capture of the data from one end and should be analyzed by the system at front end with all possible scales and speculations for quicker decisions by the management.  Following this now the trend of the development of algorithms has made shift from writing “supervised algorithms” to unsupervised algorithm, where the supervised part of the algorithm gives better insights into the new data from past data and unsupervised part concludes from the old datasets.

Process Software should be backed by the statistical analysis and predictive analytics to make artificial intelligence and to automate the decisions making ability in process(es).

Though even if organizations and regulatory bodies make standard guidelines for electronic technologies where the ample of codes are being run to capture, store, clean, analyze, and present the result in fractions to the user, will again keep on changing and evolving with growing technology. This process would leave behind the QUESTIONS and SCENARIOS unaddressed!. Manual and Automated testing of the application would not be sufficient to make application stand with data set variation.

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Artificial Intelligence – challenging human minds with rational agents!

It has become challenging for humans to beat computer systems and logics formulated behind them. Developed by humans for the excellence of processes in day to day life and for the care of population.

There are four ways of approaching Artificial Intelligence:

  1. Thinking humanly – cognitive science
  2. Thinking rationally – logic
  3. Acting humanly – turing tesing
  4. Acting rationally – rational agent

Thinking or acting deals with thinking processes or behavior, while humanly or rationally means humanly or to do the right things.

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The AI approach has been taken to such a level where robots and software are communicating with human in their language. In fact the AI’s approach is to act rationally and to build rational agents, and these agents are nothing but the robots and software.

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Gestation of Artificial Intelligence (AI) was from 1943-1955, where the AI developed in a cogitative process. First work on AI was started by Warren McCulloch and Walter Pitts in 1943, where the duo developed and worked on artificial neuron model where the neurons where either on or off to function.

“How AI has become an Industry” and entire processes has been given a cobwebbed connection to increase the production and output by many folds. None of the major processes in industries are free from software applications and machines that are guided by codes.

Challenges to be handled in future:

Though this ever growing technology is helping each and every one of us and at the same time it is keeping humans away from the nature and that’s where the natural processes are evolving and leading to a world of so many unexpected disorders, health issues.

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Quality maintenance in Software and Web industries with RCA & CAPA

Root Cause

A root cause is a factor that causes a non-conformance or deviation from a defined path and should be permanently eliminated through process improvement and analysis. Root Cause Analysis (RCA) is a tool to help identify what, how and why an event has occurred so that proper steps can be taken to prevent future occurrence.

RC can also be to target opportunities for system improvement. It can be attested that root causes are specific underlying causes that can be reasonably located and are mostly management’s control to amend and it helps generate effective recommendations to prevent recurrences.

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Courtesy: http://www.mastercontrol.com/

RC Analysis process involves data collection, causal factor charting, root cause identification, recommendation generation etc.

Resolving a quality problem could be done with correction, correction action or preventive action! These actions under regulations also require proper identification, documentation, evaluation.

Correction: is a type of action, correction is a change that makes something right, true, accurate or better. It is also defined as an action taken to eliminate a detected nonconformity.

Correction Action: is action taken to eliminate the causes of a detected nonconformity or quality problem. The deemed action is intended to eliminate the recurrence of a quality problem that has occurred. Post applying correction actions to confirm the issues is not being faced again. This is called verification of effectiveness, which manifests that the actions have addressed the root causes of the problem to reduce or eliminate their effect, depending on the goal of the CAPA.

Preventive Action: is action taken to avoid occurrence of a potential issue.

What action is being taken to amend the issue is of utmost importance in ensuring safe and effective products.

RC & CAPA is a team effort that should be address properly in most of the cases. Leaving the same unaddressed may worsen the issue(s) and later may require lots of description and time digging up the bugs and relevant parts that has been impacted.

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Next Generation Sequencing (NGS)- breaking the human genome code

So far now, it has become possible to sequence anyone’s genome cheaper and quickly with the help of latest technologies. Researchers have started gaining much into discovering the meaning of individual genomes. Though still the sequencing has not come down to an affordable price but has been sponsored mostly by the stake holders of the research projects to get into the main stream of the genomics worlds. And it has been highlighted that the individual genome sequencing would help track the rare deformities and anomalies in the gene line of human and can be engineered to treat or suppress the genes responsible for the cause.

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Concerns over the repository of the genome sequences:

  • If the genome is sequenced, who should access this?
  • How securely the sequences can be stored away from snooping?
  • How the national database should be made?
  • Would it be easy to handle fastest growing data of sequences?
  • Would this be easy to make available centrally for right access?

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Technologies that is killing the password system!

Positioning human body as a recognition tool is the current leading way of identification at every ground now. Alphanumeric and other sort of randomly generated passwords are on the verge of losing ground now. How Apple started the use of fingerprint identification in gadgets, like that now every electronic gadget would let the initiation post biometric identification to avoid any interference.

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Increasing trend in the technology has made process easy and quite fast, no doubt but changes always comes with bunch of challenges that growing technology is facing in terms of maintaining data integrity, backup of the data, analysis of the data etc.

Cryptography does help in tackling the problem upto a great extent. If there is a way to encrypt data, there is always a way to decrypt the same using other platforms and code. This growing and multiplying technology has both pros and cons. Both ends need equal attention to manage the process.

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Crowd Testing (TaaS) taking over the internal testing for better results of the software and web products

The power of crowd testing has reduced the issues and failures to a significant extent in software and sites when released in live environment. With the increase in the rise of technology and platforms, testing of the products have been replaced with crowd testers rather than various level of internal testing, that takes time and sucks most of the time in documentation. In many instances these level of testing reduces the final touch by the internal team and that further leads to the blunders and failures at later stages.

Crowd testing helps in pouring more ideas, conclusions and refining the content and helps in achieving the overall intended goal of the development. Harmonization among team members can really help develop a great product.

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Internet and mobile devices have acted as catalysts and have triggered a chain reaction also the effectiveness and ROI has increased to many folds. Well managed testing helps in validating that the final product meets the targeted quality standard. Crowd testing has become a broad and effective means of ensuring that all the bases are covered.

This way, offering Testing as a service (TaaS) on cloud is a good choice for many software firms. Crowd testing has become synonymous with community testing. It is fast growing sector for testing with flexibility, instantaneity and real world multiplatform testing.

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Crowd testing also helps in forming competition hubs, platform for idea generation, service option, and content refinement.

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How CLOUD Computing has ruled in Data Transfer with SaaS, IaaS & PaaS Solutions

Data collection, Data transfer in IT industries and Healthcare Sectors and Telco made easy…
Gone are those when calculations and data transfer and retrieval were the issues. Software automation and control has helped in a way, where the data has generated beyond imagination. Once data started generating, it came into consideration that the data or result should be in such a format that can be imported to other software for analysis and graphical presentation.

To manage the challenge of data integrity and compatibility, file conversion and multiple export options came into evolution and solved the issue. Now when we have various formats, it needs to read by the software either using the software in local machine or else accessing the same on cloud at some other location. Here this cloud technology has given a platform, where huge chunk of data like of DNA sequences, Terabytes of values can be analyzed and represented in a required format. Cloud has helped linking multiple data generating centers to connect and store their generated data at once central location, storing and accessing has become easier.

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Using software on cloud has many advantages:

  • Can be less expensive compared to buying soft we and hardwires
  • Can be used from any of the computer or device with an internet connection
  • No need of large internal storage system
  • Updates occurs across the service
  • Self service provisioning
  • Elasticity
  • Pay as per the use

It does have loopholes too!

  • Many security issues
  • Terms and conditions of services
  • Privacy policies
  • Data leakage issues

Cloud services

Platform as a Service (PaaS): This is a way to rent hardware, operating systems, secured storage and network capacity over the internet. Where the service delivery model allows the customer to rent virtualized services using the services for running applications.
Infrastructure as a Service (IaaS): is a provision model where an organization outsources the equipment used to support operations, storage, hardware, servers and networking components. Client pays on the agreed basis and service provider owns the equipment and manages housing, running and maintaining of the same.

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How learning Bigdata concept has helped industries handle huge datasets

Bigdata concept like Hadoop, Hive, Pig, Hbase, Sqoop, Mahout, Yarn etc. has helped manage analyzing huge chunks of data from various sources.

What is big data?

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There is nothing new about the impression of big data that is in talk since at least 2001 and has evolved to many folds. In a nutshell, Bigdata is nothing but your data or any company’s own data. It is the information owned by the company obtained and processed by new techniques to produce values. Any bigdata expert would define this using three V’s i.e. Volume, Velocity and Variety and this concept was proposed was Doug Laney to thrown light into the challenges of data management. In the year 2013, Mark Van Rijmenam titled why the 3 V’s are not sufficient to describe big data and he added more V’s i.e. Veracity, Variability, Visualization and Value to the definition.

If we talk about the generation of the data in a huge amount followed up with management and structuring was created in the past three years. And it is not false to say, that the amount of data in the world will continue to double or keep on increasing many times.

What companies are doing to make best use of information?

Bigdata constitutes significant information that may help pave new business or opportunities to serve the population. It helps corporate in making decision and taking further steps into their business and endeavors. And it has become really necessary to have statistical figures on the desk of managers to risk money in new start up. Bigdata has indeed being called trendsetter in the business of data management, analysis and storing and retrieval.

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SOFTWARE – Quality Management – An amalgamation of all systematic series of activities & processes

Computers and Software are omnipresent. In most of the cases computer technology is implanted and we don’t even imagine where and how we are utilizing those technologies in day to day life. But we are doing it every bit of time. Our day to day activities are almost dependent on software and gadgets. We might admit the same or not! but really software and technology is governing our world and society. This trend would not change and would continue impart values in our society and system and this will go on with research and development to get improvement at every step.

Key reason behind the change!

The ever growing and evolving trend has ofcourse made many things so easy that productivity and quality has leaped to highest point of satisfaction. But sooner or later system is going to get disrupt and disease would spread, security would reduce and this all would disintegrate the society and system.

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Control over the management of the entire system and the concept of embedding technology at every step is of utmost importance to take things ahead in a right way. It is highly important to make sure that the system and software should run as proposed. A single loop hole can make the entire development suck in giving the expected result.  A right quality of the software can help us stay in control and productive in a positive way.

Software Quality is the discipline that ensures that software that are being developed, deployed and used bears the right quality. It must be noted that flowing with the speed and technology should not be the point of concern when we are developing something, but should think in an ethical way too, it should not harm the society and should not lead to an imagined output that might put something in dangerous situation.

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