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

Use of AI in retaining employees

Employees are the most valuable asset in any organization and your most valuable employees are often the quickest people to leave. The author in this article explores how you can use artificial intelligence to create systems that help meet your employees’ intrinsic needs and build the supportive and challenging environments that employees crave for. Read more at:


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Why Big Data is important

Nowadays, in business, people are using artificial intelligence and multimedia visual marketing, and these are also connected to the concept of Big Data as every action of internet users take generates a data trail, and the amount of machine-generated data is growing too. So, using data effectively can give businesses an edge in today’s competitive environment as analyzing Big Data helps them to achieve better results in many areas of business with minimum wasted effort and costs. Read more at:


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Most prevalent languages for Machine Learning and data science

Careers in machine learning, Data science, artificial intelligence, deep learning and many more are considered as one of the best choices to pursue. Now these technologies and the related jobs are considered one of the hottest and best jobs today. So, here are the list of top 5 languages prevalent in market for data science, machine learning etc.

1. Python

2. R

3. Java

4. Scala

5. C



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Machine Perception: An era of Smart Robotics

Smart Robotics is becoming an evolving field in the area of artificial intelligence. Modern robots have become far more intelligent and adaptable in a continually evolving environment than their predecessors which is attributable to machine perception plays an indispensable role in their development when used in conjunction with more sophisticated machine learning steps.

Data scientists and AI engineers must overcome certain challenges to improve the future of robotics. According to Rewired, there are ways to improve machine perception to fortify smart robots. Treating machine perception algorithms as a passive system coupled with poorly thought on assumptions were the grave mistakes made by programmers. As a remedial procedure, learning as a proactive, multi-sensory process in being borne in mind.  Dependence on antiquated sensory systems have been replaced by new sensory systems to process inputs. According to Russell graves of CoSMoS Laboratory, improved positioning and quality of data forms the building blocks of modern machine perception. 

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Tips for Getting More Benefits Out of CRM

Nowadays, CRM is surrounding marketing, customer service, business intelligence and several other functions. Some CRM systems can also be transformed into enterprise resource planning solutions with the use of apps and third-party add-ons. CRM has come a long way and now can include artificial intelligence, automation, data enrichment through aggregation of contact information from other sources. This article explores some tips for getting more from CRM. They are:

1.       Automate processes and data entry

2.       Clear the clutter of unnecessary data fields

3.       Integrate customer behavior

4.       Use activity management within the CRM

5.       Revisit integrations frequently

6.       Implement automation


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New Innovations in CRM

Nowadays, business is moving faster and getting more demanding due to the increased competition and consumer expectations that come from online and mobile-centred economy. Now, meeting these demands requires managing customer experience at every touch point, and that is in turn putting added importance on automation, artificial intelligence, big data and analytics. CRM is also coming up with some innovations. Here are five of the CRM innovations which are coming up and will help your business to handle today’s market demands. They are:

1.       Automatic Workflow Adjustment

2.       Chatbots and Conversational Interfaces

3.       Automatic Data Entry

4.       IoT Integration

5.       Customization


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Google Pixel 2 or iPhone 8?

Google came with Android O and Apple came up with IOS 11. So, which one’s winning the race? The nutshell answer is Android O. A comparative study has been done to show this. Android O: multitasking, notification dot on the app icon, intelligent text selection, auto-fill, prolonged battery life. IOS 11: pay through iMessage, collaborating speakers, beautified AR effect, live photos, less memory clogging, DND while driving.  Both are equipped with voice assistant, but Google is a step ahead and can recognize objects and you can type queries relating to those objects if you don’t want to speak them. Apple is way backdated with AR and VR as compared with Google who uses AI. Read more at:


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Effect of Artificial Intelligence on Financial Services

As AI is moving forward the need for marketing in financial services is diminishing. Generative tools use computers and algorithms and are widely used within Financial Services. So why does that mean financial services marketers are doomed? AI does financial work by simply crunching thousands of data points, factoring in current constraints, predictive models for how things are going to change, and the individual’s goals. AI is making all decisions. Marketers are probably not going to start marketing to AI. More likely, marketers would shift focus to trying to influence the parameters humans input into the AI.  By providing an appropriate media mix to AI we can achieve goals within the budget. AIs are used by both consumers and the companies. Consumers will leverage AIs to optimize their lives and businesses will use AIs to create more personalized products and services. In this future, marketers will ultimately end up marketing to the AIs directly.Read more at :


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Chatbots And Social Media Marketing Strategies

Nowadays, marketing is not possible without social media and the chatbot has become the newly-adopted social media tool. Chatbots helps in your social media marketing strategy and also increases website traffic and sales while providing Artificial Intelligence assistance which in turn will help you to communicate better. Use chatbots as an analytical tool and optimize it for conversions. Read more at:

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The Rules Of Salary Negotiation

Salary negotiation is a key to get to the top of the rat race as the World Bank data suggests that 69% of jobs in India are suspected to be taken away by automation. The World Economic Forum predicts 35% of top professional skills today would be replaced in the near future. At present, every person is required to re-assess their skills and re-skill themselves. If automation will disrupt several jobs, there will be technologies like IoT creating many more jobs necessitating critical problem solvers. It is predicted that advanced robotics, artificial intelligence, advanced materials, biotechnology and genomics would be the next frontier of employment. Only with requisite skills in these disruptive fields and a multi-disciplinary approach could empower future job seekers to become critical organizational assets. Read more at :


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Black box and Artificial Intelligence

Subsets of AI are diversifying and algorithms are growing advanced. AI had an alarming impact in many instances. Certain applications of AI are called black box because it is difficult to understand how the result have been generated. Decoding the black box technique involves optimizing a given function in isolation, and sharing it as necessary. This makes the work a lot easier and scales the data. Firms need to make people aware of AI's applications in order to make it more transparent. AI cannot be completely trusted with certain applications. In future, we have to embrace AI and develop trust on it because it has many advantages and black box is a positive step in this direction. Read more at:


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IT operations: problems and solutions

The main responsibility of DevOps and IT operations teams include solving problems and facing challenges which is becoming tougher by each day. This is where real-time and centralized log analytics come to the rescue. It helps them in understanding the essential aspects of their log data, and easily identify the main issues. While Artificial Intelligence (AI) was a big thing a few decades ago, it is now being commonly used. As IT operations becoming more complex, AI is becoming a powerful and essential tool. One solution can be to have a platform that has collected data from the internet about all kinds of related incidents, observed how people using similar setups resolved them in their systems and scanned through your system to identify the potential problems. Cognitive Insights can be introduced, this technology uses machine-learning algorithms to match human domain knowledge with log data, along with open source repositories, discussion forums, and social thread. Read more at:


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Opinion mining: an emerging field in data analytics

With the increasing availability of data in the present digital age, a new science of opinion mining is emerging. It is based upon the use of Artificial Intelligence (AI) to mine public opinion for sentiments as well as the topics driving that sentiment. This can be carried out in two ways: the first one involves the exclusive use of AI to structure the data, while the second one involves the use of AI along with processing of data through a team of people to verify the data for sentiment and the topics driving the sentiment, since AI could struggle to understand the nuances of human emotions. So, the field of data mining can be used by governments, global organisations, media and businesses to shape their strategies efficiently and, measure the public’s/consumer’s satisfaction of their policies, products, services and brands.Read more at:


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Profitable business analysis- how to achieve it

Business analytics help in taking decisions. Business intelligence involves analysis of prior analysis and is used to support tactical decision making. Machine learning involves processing historical data to make future predictions. There is scope to add applications to deal with consumers. Unless analysis is done in production application the business will not realize efficiencies. Such analysis can speed up daily activities. The prescriptive analysis makes best use of resources by establishing how processes should be executed. Artificial intelligence supports automation of processes and decision. Machine learning is under AI, but more advanced. The main issue is that the analysis and intelligence should be integrated into the working environment. Methods, culture and discipline will always be the key challenges. Read more at:


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