SigmaWay Blog

SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

Growth stalled? What to do next

For any budding company or an industry, the ultimate driving force that can help them survive the thorny path of competition is ‘growth’. A particular company may not last long without growth fuelling its fire of success. It not only ensures easy and faster cash transaction but also makes ways for new project, satisfied customers and talented new hires. However if growth halts once, a company’s future is fully dependent on its founder’s ability to restart the engine of success. In fact in many cases half of the new businesses close down in five years in absence of the driving force.  Question arises on how to take up a company from the path of despair and jumpstart growth again. Let’s look at the following tips:

·         Adding empathy screening to hiring process- A better understanding among the workers of the company can lead to better anticipation of needs and improving productivity thus inevitably leading to faster growth processes. In fact empathetic behaviour helps to evaluate others’ agendas and deliver something that meets the needs of all.

·         Investing in relationship not in sales- Where authenticity is craved by the modern customers, one should promote content in such a manner such that it leads people to have a deeper connection to the brand. Just a mere commercialisation with clever camera edited marketing skills won’t help accelerate growth of the products much if it doesn’t make any sense for the brand.

Hence putting together a strong team and leveraging the most attractive features of a company can put off the stagnating growth and initialise the processes of success again.

Read more at: https://www.entrepreneur.com/article/316088

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China’s Laser Blaster

Signs of exhilaration are heightened among the ‘Star Wars’ fans as China has invented a new weapon called ZKZM-500 similar to the laser blaster in the movie. Weighing more than 6.6 lbs., the 15 mm laser gun can fire more than 1,000 laser shots, each one lasting up to 2 seconds. Although the weapon is claimed to be non lethal by the Chinese government, the invisible energy beam produced by it can cause instant carbonization of human tissues and skin. Infact it has the ability to penetrate through windowhs thus igniting gas tanks and burning anything nearby. However burning hole through a body will take several zaps by the weapon. The gun can have wide usage such as it can be used by the Government to fire illegal banners in a protest or setting fire to the clothing of the protester. Although ready for mass production, its creator ZKZM Laser hasn’t yet found a licensed company ready to take up the $15,000/unit worth guns. The weapons will be in future handed over to the Chinese army and police.

Read more at: https://www.livescience.com/62973-china-laser-guns.html

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Big Data in Aviation Industry

Fifteen years ago it was only fair for the airlines companies to keep record of the ingoing and outgoing flights only. But now let’s imagine a sudden storm hitting the East Coast today. This would imply that several flights will be delayed. Hence keeping up to their standards and adding a value to the every penny the passengers have paid would involve several entailing jobs like determining the flights to be connected with the airline, baggage transfer time, the number of transferring passengers, the flights that are coming from and so on. It naturally means a proliferating amount of big data sifting and shifting from a constellation of different sources. A Boeing 787 alone creates a half a terabyte of data every day. Big data in aviation are useful in many cases such as:

·         Fuel Efficiency- Fuel is the second highest expense for airlines and estimating power has developed to a point where airlines can congregate and process the enormous amounts of data they need to analyze on a per-trip basis. It is hoped that data mining will produce actionable intelligence around decisions such as adding or subtracting flights to routes, setting fuel loads for each aircraft, and selling additional passenger tickets. 

·         Smart Maintenance- The big data, including mechanic write-ups, shop findings and in-flight measurements, helps the airline company to plan equipment maintenance with minimal disturbance to flights.

·         Airline Safety- A data collection and analysis program named Data4Safety has been recently launched by The European Aviation Safety Agency (EASA)  to detect risks using a amalgamation of safety reports, in-flight telemetry data, air traffic surveillance information, weather data and so on.

Read more at: https://hortonworks.com/article/how-big-data-in-aviation-is-transforming-the-industry/

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Predictive Automotive Analysis

The use of predictive analysis is widespread including in connecting car industry which provides both opportunities and challenges for the automotive industry. By using Telematics and infotainment systems, connected cars increasingly stream data into the cloud. Each connected vehicle is expected to generate more than 25 gigabytes per hour as the dizzying array of smart IoT sensors are coming into the picture. Predictive analysis in automotive industries is enabling connected cars to stay more on roads rather than in shops. Some of the ways in which predictive automotive data analysis is driving the growth of connected car industry are listed as follows:

·         Predictive Maintenance-Predictive data analysis can spot maintenance issues before they occur by leveraging data from warranty repairs with existing vehicle sensor data. This is done by pulling in data from virtually every vehicle, comparing the information with warranty repair trends and finding meaningful correlation which is otherwise impossible to be discovered by humans.

·         Predictive Collision Prevention-By utilizing big and fast data, latest sensors and car-to-car connectivity, predictive analytics technology may completely eliminate the possibility of accidents in the future.

·         Connected Car Cyber Security- Predictive analytics is efficient in securing connected cars in the sense that it is able to identify patterns of attackers’ behavior. It not only looks for an intruder to repeat the same behavior as pervious attackers but also searches for a combination of behaviors that are inconsistent with what would be expected of an authorized user.

Read more at: https://igniteoutsourcing.com/publications/predictive-analytics-in-connected-car-industry/

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The two hands of the businesses: big data science and analytics

Big data and analytics have been the biggest contributor in the recent years. By the end of 2020, the big data volume is going to reach 44 trillion gigabytes. Data analytics provides many innovative solutions for insurance, FMCG, retail and financial services. AI and machine learning helps in predictive analysis and helps in making accurate predictions for the growth of the business. Big data science and analytics have advantages of speed and compiling big volumes.

For more information visit:

https://www.entrepreneur.com/article/316057 

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On demand start-ups: failure or success? On demand start-ups: failure or success?

Technology has helped develop such apps which provides services at the door right from cabs to groceries. Provision of other services like plumber, electrician and other maintenance services still are unavailable on apps. Providing these services is not a good option because if we see the calculation then the overall costs is more than the money paid by the customer. To break-even the customer should use their services at least 10 times to average the price to 44 Rupees. There are other factors too like loyalty of customers and discounts which is definitely not sustainable for the company. This market is unorganised sector in India and has a lot opportunities. Customers complained about quality of services and prices and hence this needs to be rectified.

For more information visit:

https://www.entrepreneur.com/article/308191 

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Top 5 languages to learn for ML

The power of machine learning is growing exponentially. Almost no industry domain is remaining untouched with the wonders and powers of machine learning.  Machine learning is just an application of artificial intelligence whose algorithms helps to analyze the historic experience without being explicitly programmed to predict the future affairs. Before jumping into the world of machine learning, it’s important to know which languages are being used to analyze the data and predict the future. Here are those 5 languages which are being using for machine learning: 

1. Python

2. R Programming

3. LISP

4. Prolog

5. javaScript

why and how are these languages being used for machine learning? For detailed information,

https://www.analyticsinsight.net/top-5-machine-learning-programming-languages-you-should-master/

 

 

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Data management over cloud

Although cloud storage has benefited the businesses in intelligence enterprises but still it shouldn’t be trusted blindly. Cloud storage techniques have helped digital data storage and the changes are remarkable.

The 2 challenges that are connected with cloud storage, cloud lock-in and management complexity are:

• Cloud lock-in: Failure to transfer data from one cloud storage facility to other.

• Management complexity: The inability to perform proper management of available storage environments.

Following are the solutions to these problems that may be seen as unsolvable.

1. Gateway device: It behaves as an agent between the on-premise storage and the cloud storage.

2. Hybrid cloud: With the help of hybrid cloud, cloud storage acts as an extension to on-premise data storage.

3. Multicolored controller: It permits the data to be seen at the same time.

For more information go to,

https://www.analyticsinsight.net/how-to-solve-the-challenges-of-data-management-on-cloud/

 

 

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The secrets that lead to the success of Six Sigma

Six Sigma and Lean is being used in every industry right from software development to multinational companies. As far as the history of Six Sigma is concerned it was developed in the year 1900. Officially this product was launched in 1980s to reduce variability. Lean deals with data, philosophy and also removes the waste that creates a good environment. The secrets that link consumers’ satisfaction to company’s strategy are:
• Customer’s value
• Achieving goals of the company
• Increasing productivity through motivation of the company

    
For more information visit:

https://blog.edx.org/six-sigma-lean-3-secrets-success?track=blog 

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Economic productivity and effects of Artificial Intelligence

The economic productivity of the country should rise up if there are improvements in technology and artificial intelligence but this is not the case. When the industry employs AI then this lead to more leisure on people’s part and making them useless. According to a survey it has been found that there is a rise in inequality in wages and hence AI needs to be implemented. There should be greater productivity gains but it is dipping. The reason could be slow commercialization. Though it displaces labour but it creates jobs in other sectors. Automation does not replace jobs but it does a part of the jobs.

For more information visit:

https://analyticsindiamag.com/why-has-the-economic-productivity-not-picked-up-despite-the-advancements-in-ai/ 

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How revolution in cloud computing pushes surprising business growth?

Nowadays businesses have opened new gates for certain innovations using cloud computing technology with a proper and selective approach. Most of the IT executives are now entirely focused on how to make cloud a way to achieve their business goals and their entire focus is on cost optimization instead of cost management. In terms of transformation, the cloud has been a central to many organizations. Big data technology has allowed storing and recapturing of the vast amount of information. Regardless of any sector, most of the organizations have transferred all their data to the cloud. But still, most of the executive’s are reluctant to adopt cloud due to security concerns.

Businesses can achieve maximum growth only by accessing, controlling and analyzing all flaws present in the cloud network. That is why multi cloud is more preferred.

Due to digital transformation most of the companies have enforced cloud services to become more profitable.

For more information, go to:

https://www.analyticsinsight.net/how-innovation-in-cloud-computing-drives-exceptional-business-growth/

 

 

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The correct outlook to unite your organization with cloud computing

Nowadays for every organization it has became essential to be associated with cloud as a platform, infrastructure and service. Cloud computing is a very helpful tool as it can be used to create new revenue opportunities for the organization. This era of cloud computing has expanded the efficiency of the computing by reinforcing memory, processing, bandwidth and storage. If you haven’t dispersed your organization to the cloud yet, these can be the right footsteps to follow:

Step 1: create an assessment

Step 2: choose a right cloud environment for your business

Step 3: decide your cloud architecture

Step 4: choose the right cloud computing provider

Step 5: make a strategy for risk mitigation

Step 6: make a plan for mitigation  

Step 7: execute your computing plans

Step 8: examine the implementation

Need a better understanding of these steps?  visit:

https://www.analyticsinsight.net/the-right-approach-to-integrating-cloud-computing-into-your-organization/

 

 

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Revolution in the world of manufacturing with the merge of machine learning and 3D printing

Of course we have achieved 3D printing, but somehow we are still not able to produce a metal object which is capable of replacing the real world articles. Now implementing machine learning with 3D printing we have the capability to have real world objects replaced by objects produced by 3D printers. In the world of manufacturing researchers are planning to produce self correcting and repairing machines. There can be multiple approaches to have self-correcting machines. What are they? 

For more information, visit:

https://www.analyticsinsight.net/the-confluence-of-machine-learning-and-3d-printing-will-revolutionize-manufacturing/

 

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How AI can be used to forecast severe brain disorders?

Whenever it comes to complications, we all know human brain is the most unpredictable and complicated organ of the human body. Any brain injury leads to damage of millions of cells due to lack of oxygen in the body. Such damages require immediate attention of the doctors. But somehow, making out and analyzing those reports results to the latency which more often comes out as life threatening news for the patient.   

So, how AI can contribute its role here? For increasing the efficiency of the workflow some AI algorithms has been applied to the machine which are now capable of detecting the abnormalities requiring urgent attention of the doctor.

Want to know more about how actually AI and deep learning is applied to radiology? 

Go to:

https://www.analyticsinsight.net/how-artificial-intelligence-predicts-life-threatening-brain-disorders/

 

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Loyal customers are the key to a successful business.

A Business owner wishes to know more about his/her's customers, wants them to keep visiting the business more, and increase the purchases. To achieve such goals, loyalty programs are created. So basically marketing strategies involve in getting the customers and getting them to return. Loyalty programs are structured marketing strategies. It is designed to encourage customers to shop at or use the services of businesses again and again. To know more visit at: https://www.business2community.com/loyalty-marketing/do-loyalty-programs-really-create-loyalty-02049183

 

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Human Capital Management Software simplifying People Management!

Employees are the company’s most important asset and the HR department is critical in managing them. The HR department has huge responsibilities, right from recruiting employees to ensuring the employee’s rate, all the responsibilities fall under the HR department. With the pool of functions that an HR has to perform, the best would be to provide them with sophisticated HCM software which would make their work comparatively easy and more efficient. It is a tricky business to choose the best HCM software. We can either choose to have a specialized tool to perform one function efficiently. Or, we can go for a consolidated tool to help you manage all the HR process under one umbrella. These software save the company time and money, making the HR department more efficient.

To know more visit at: https://academy.whatfix.com/human-capital-management-hcm-software/

 

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Autism Diagnosis using Artificial Intelligence

Autism being a spectrum or developmental disorder characterized by lack of social skills and repetitive behavior is being diagnosed using several methods in order to identify the onset of this disease. One such method is used by Autism Diagnostic Observation Schedule which inspects videotapes on the basis of an assessment between an examiner and a child for understanding the child’s behavior. According to a paper published in Science Translational Machine by researchers from the University of North Carolina at Chapel Hill and Washington University School of Medicine, doctors could precisely forecast which child might develop autism before hitting 24 months and with a 96 percent accuracy rate. A fully cross-validated machine learning was developed which used the scans of the 6-month-old infants. 59 high risk brain scans were taken over 230 regions and the whole brain was mapped creating matrices of functional connectivity from each child’s MRI data.  The algorithm further analyzed the brain scans of the 6-month-old infants and it properly predicted 9 out of 11 infants had the symptoms of autism at 24 months, with a sensitivity of 81.8%. Such data-driven approach is a good indicator of predictive measure that suggests that AI and machine learning could someday possibly recognize diseases with accurateness and extend treatments for the mass and maybe halt the headway of the disorders themselves.

Read more at: https://www.analyticsinsight.net/artificial-intelligence-machine-learning-can-be-used-to-predict-autism-in-children/

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Big data in Google’s Multilingual Semantic Indexing

Google has been dominating the search engine industry over the years, though it has been frequently criticized of not providing search results in non-English languages. To cater to the problem, it has resorted to semantic indexing thereby becoming proficient at providing multilingual search results. The spectrum of search contents have been widening with time thus hinting at an expanding and trending macro environment. The search engines use algorithms which are solely based on Artificial Intelligence which would be rather simpler with limited pre-defined inputs. In its quest to understand the true meaning of different search queries, the algorithms are required to understand the contextual meaning behind various pairs of words which is attributable to deep learning. Despite capturing 70% of the search engine market globally, certain discrepancies arise due to regulatory policies. However, according to Shout Agency, the core problem is not the structure of algorithms as Google can make educated assumptions indexing any language but discrepancies in search results persist. The crux of the matter entirely stems from the fact that Google has had limited opportunities to conduct deep learning in some language than others. A potential risk is involved due to smaller user base and fewer Google employees that can understand the language enough to determine the worth of the content which lowers the chance of Google to conduct manual penalties for content. This could lead to greater pervasiveness of spun content throwing away algorithms dependent on deep learning.

Read more at:  https://www.smartdatacollective.com/google-search-algorithms-use-big-data-multilingual-latent-semantic-indexing/

 

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Artificial Intelligence lends to Agile Machine Learning

Of late, Agile methodologies have been taking root in data science boosting complex collaborations between data scientists and other developers. Agile can be easily ported over to Machine Learning and Artificial Intelligence domains due to its feedback-heavy, iterative nature and given that incessant improvement is an innate part of AI. Such methodologies are characterized by fast feedback loops and short development sprints. Agile projects, in distinction to old-school waterfall approaches, involve error correction and cyclical stakeholder input and primarily focuses on short term goals rather than the long-term view. AI researchers should think of research as an iterative, evolving process to remain receptive and adaptive as per Agile’s basic tenets. To ensure that projects do not grind to a halt, maintaining a buffer of solutions for implementation is a priority as data scientists work on multiple projects, each taking months to complete. The iterative nature of Agile well captures experimentation as a core part of AI and ML projects. Agile maximizes value throughout the development process.

Read More at: http://www.dataversity.net/case-agile-machine-learning/

 

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Few CRM hacks every entrepreneur should be using

Budding businesses often uses personalization processes that relies on accumulating customer data from third-party sources but that era is coming to a close. CRM systems can be significant sources of vision that empowers and enable companies to see their data from all angles but at the same time can be difficult to use and maintain. Few tips to convert CRM systems from potentially confusing resource into a powerful weapon are as follows:-

·         Tell the software what to streamline-

CRM automation is better than the manual processes in the sense that it can remove the obstacles involving tedious and time consuming works, by importing data, making smarter schedules and compiling related data.

 

·         Learn to spot at-risk accounts-

CRM software is the ideal instrument to track customer engagement as it allows employees to help clients when things look bad. For an example, it can set up the flags for different triggers, such as repeat complaints. The software can alert sales representatives when customers set off one of the triggers.

·         Use Robots to make CRM adoption-

Virtual assistants such as chatbots, powered by artificial intelligence, can network with CRM systems to set appointments, add client information to files, and locate information without forcing users to sieve through data manually. 

 Utilized efficiently and correctly, a CRM system can transform from an equipped essential into a competitive advantage.

Read more at: https://www.entrepreneur.com/article/312994

 

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