SigmaWay Blog

First question that must be popping in your mind is what is SLAM? SLAM stands for simultaneous localization and mapping. Wherein, a device or robot can create a map in real-time as per its surrounding and position itself within the map. SLAM is a technology which is developing under virtual and augmented reality. SLAM technology requires number of algorithms which can simultaneously localize and the objects.

Why do we need SLAM? What are the applications of using SLAM technology? These questions will be answered here:

https://www.analyticsinsight.net/future-ar-slam-technology-slam/

Under the implementation of data analytics, AI and robotics the concept of “smart airbase” is being discovered by RASF in a treaty with defence science and technology agency (DSTA) for sustaining power for armed forces. This amazing concept includes the drones which are capable of detecting damaged aircrafts. There are such more examples of advances in defence section with the adoption of AI, robotics and data analytics. 

Want to know more about it, visit:

https://www.analyticsinsight.net/singapore-air-force-and-navy-embraces-data-analytics-ai-and-robotics-to-improve-operations/

Digital twin technology is actually the virtual replica of physical devices. This technology can help us in manufacturing, energy, transportation and construction. The complex items like aircraft engines, offshore platforms, trains and turbines can also be constructed and established digitally before being physically developed. These digital twins could also be used to help with maintenance works. Let’s say, technicians can use digital twins for testing. So, how it works? How it gets started? What are its applications?  Why it is important to us?

For more information go to:

https://www.analyticsinsight.net/digital-twin-technology-important-big-data-age/

How the Amazon is able to raise itself as one of the titanic disruptors in retail space? With its warehouses, full of robots is actually enhancing the speed and efficiency of logistics operations. FedEx is also tracing the footsteps of Amazon. The deployment of mobile robots inside FedEx is showing up how customer’s E-commerce habits are improving the retail and logistic sector. Commonly companies are making use of robots as store-service robots, inventory robots and delivery robots.

Robots are actually complimenting the human colleagues’. But the main objective of retail industry is to make profit margins and increase the productivity using robotic automation technology. 

For more information visit:

https://www.analyticsinsight.net/how-worlds-biggest-companies-use-robotics-in-supply-chain/

Seems like android has been around for an extremely long time. The fun fact about android is that android was originally made for digital cameras. Android has transformed and evolved a lot over time. There are a lot of different versions, and every version of Android is a code name, which many people use instead of the version numbers like Android8.0-8.1, Oreo,Android7.0-7.1.2,Nougat:Android6.0-6.0.1,Marshmallow,Android5.0-5.1.1, Lollipop. Each one is named after a dessert or some other form of confection, which is more for fun than anything else. To know more visit at:  https://www.howtogeek.com/345250/whats-the-latest-version-of-android/

The implementation of Business Intelligence Tools have gained enormous importance, as there are terabytes of data incoming from many sources from all over the world. With such quantities of data at their disposal, these companies want to analyze and track sales dynamics, trends, and analyze the efficiency of their business decisions. It is vital to perform these operations in a timely manner, so that the analysts can work with these data. Big complex data can now be easily managed through the help of business intelligence tools by any small or big organizations. The collection of data are analyzed and are converted into simple reports, which helps the organization with valuable insights, which indeed helps them in earning necessary profits. To know more visit at:  https://financesonline.com/15-best-business-intelligence-tools-small-big-business/

Market intelligence is the process of gathering data from the company’s external environment to stay ahead in the competition. Outcomes of market intelligence are market opportunity, market penetration strategy, and market development. Building a solid market intelligent system is vital to having the information necessary to compete and win in the business battle ground. Market intelligence deals with a lot of insights. The main sources of raw data collection for market intelligence are sales log, surveys and social media. To know more, visit:  http://www.dobney.com/market_intelligence.htm

Digitalization has become a global movement and initiatives are being set to accelerate the rate of adoption. 2030 has been declared as the target and many initiatives are already on their road. One such automation process that can that can change everything significantly is the business automation process. From improving customer experience to cutting down cost, business automation has the power to help the firm grow. 

However, automation efforts are only beneficial if the CIOs make right investments and decisions. It is often seen that with a wish to automate, many leaders often make wrong decisions which could cost them potentially higher than excepted.

The three business goals that investments in automation will help are:

1. Digitalize and optimize operation
2. Create and act upon advanced insights
3. Drive business technology innovation.

Read about them at https://www.techrepublic.com/article/how-to-automate-your-business-3-critical-steps/ 

Data Science is a new field of interest and used in every sector. Whether it is a business, production line or a tech company, each of them wants someone to analyse their data. This would further help them to make decisions. Even though there is so much need of data scientist, still the number of data scientist is low. There are many characteristics that could define a good data scientist. 

Few of them starting with C are: Curious, Careful, Clever, Confident, Creative, Capable, Communicative, Considerate, Candid and Collaborative. 

To know further about these words visit: https://medium.com/@tableaucoach/characteristics-of-a-data-scientist-ten-cs-4e3b185cc7cd

With existing systems and technology it is often difficult to manage massive amount of data by various industries and organizations. Keeping in mind several aspects such as cost reduction, customer experience improvement and increase in conversion rates, companies often need to derive meaningful conclusions from the data collected and establish a connection between them. This linked data is also referred to as journeys. Journeys improvise on well-grounded business decisions by pointing out the improvements needed after looking at the customer transactions as a whole. Journey Science facilitates anyone, to be a Journey Scientist, regardless of their skillset and enable them to easily generate an intelligent dataset that includes the commonly understood business context in an enterprise. Leading telecom businesses are implementing the Journey Science concept through a multi-channel, end-2-end view and linking together structured and unstructured data back to their strategic objectives, and quickly modifying them to ensure they cope up with the evolving customer demands efficiently.

Read more at: https://www.datasciencecentral.com/profiles/blogs/journey-science-in-telecom-take-customer-experience-to-the-next

In today’s business world, companies generate a lot of data. Now, we now have things like social media and cloud based business services and they all generate tones of data, which is the biggest challenge for BI. Business Intelligence (BI) refers to the tools, technologies, applications and practices used to collect, integrate, analyze, and present an organization’s raw data in order to create insightful and actionable business information. The purpose of Business Intelligence in a business is to tackle with the questions as to what are its main benefits. Read more at: https://financesonline.com/purpose-business-intelligence-business/

In an organization it may seem that the processes are ordered and it runs smoothly, but the affects are not always in line with the expectations. Companies expect and get results from process improvement, Business process improvement (BPI), also known as functional process improvement is a strategic planning methodology which aims at identifying the operations or employee skills which would eventually lead to smoother procedures and more efficient workflow for the overall growth of the business. Its main purpose is to meet customer demands and business goals more effectively. Read more at: https://financesonline.com/purpose-business-intelligence-business/

The world of artificial intelligence is so much exciting. So basically Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. In the year 1956, John McCarthy coined the term “Artificial Intelligence” and defines it as "the science and engineering of making intelligent machines." Precisely AI is a machine with the ability to solve problems that is usually done by us humans with our natural intelligence. AI is a broad branch of computer science. The goal of AI is to create systems that can perform intelligently and independently. Read more at: https://www.sciencedaily.com/terms/artificial_intelligence.htm

The online commerce industry has been growing at an unprecedented rate which is attributable to big data. Alongside exploring the benefits of deep learning and predictive analytics, small businesses, working with smaller budgets, should consider using big data to reap the most bangs for their buck in terms of highest profitability. Over the past few years, e-commerce companies have invested titanic amount in big data and have earned record profits. For example, according to Statista, Amazon in 2017 netted a profit of nearly $178 billion as compared to $136 billion in 2016. Walmart, too, experienced nearly a 44% increase in revenue attributable to more resource allocation to e-commerce. Small businesses primed for growth are also capitalizing on the surge in online payments and big data e-commerce to get their slice of the profits as well. A research by eMarketer, estimated e-commerce sales to rise upto $2.8 trillion by this year. Surely, e-commerce will continue to smoothen its way to dominance with consumers on board. Small businesses can extract certain benefits like building brand awareness, improving customer confidence and greater net impulsive buys. The propagation of big data ecommerce options is one of the biggest which has paved the way for more valuable payment systems.

Read More at:  https://www.smartdatacollective.com/small-businesses-use-big-data-ecommerce-solutions-success/

With the development of data-related technology in recent years, objective data analysis has not been able to overcome the hurdle of managing human relationships. It is indispensable to focus on qualitative human characteristics to opine about an employee in addition to performance numbers. In recent times there has been a sheer rise in demand for this kind of an analysis, even from the business perspective which would assist managers to coordinate and understand employees better. The major challenge facing data is to tackle an issue that has historically been impossible to be reduced to numbers. With a large volume of data, collected across multiple dimensions, even a rudimentary algorithm can point out parameters that could predict human behaviour. At the intersection of multiple data related disciplines including data mining, statistics, machine learning etc, a sophisticated system could be produced to make sweeping predictions about a group’s future behaviour. In a nutshell, predicting human behaviour needs complete understanding of the complex personality traits and emotional states. Moreover we aren’t naturally acclimatised to study subjective factors  that is easy for predictive analytics algorithms to parse. The transition from quantitative to qualitative data analysis calls for a more intensive method of data collection. By analysing the human behaviour, analytics businesses can become better managers, negotiators etc.

Read more at: https://www.smartdatacollective.com/how-big-data-could-soon-help-manage-human-relationships/