SigmaWay Blog

Today’s generation is health conscious and use wearable devices to track their fitness levels. This constantly generates data and we should be able to draw a comparison on different datasets or data collected from various devices. Lumo BodyTech, a fitness related tech company, created a platform (Lumo Motion) to analyse such data. People can monitor, regulate their health and get accurate advice. Lumo Back and Lumo Lift tracks the posture and combined data can be used to learn about the best posture. Even though the progress is limited but with growing number of products joining the platform, data is comparable from a wider range. Read more at: https://readwrite.com/2017/06/28/iot-will-let-you-understand-your-workout-data-better-hl1/

One of the common business challenges is that the required information by business users is not provided fast enough. The most commonly used company’s data structure is an Enterprise Data Warehouse (EDW), where when information is required, a data mart is created in a separate database, this process is problematic due to the cost of maintaining multiple databases and also the integrity and consistency of the information stored is questionable. However, the delay between the time that the information is required and when it is provided is the real problem. So, the following changes must be made in order to succeed. An information system that transforms data into relevant information very quickly should be provided and all databases should be centralized from the same point. Also, real-time information should be provided and the time to market with short and agile projects should be improved. And finally, new sources of information of different types should be incorporated. Thus, the companies should consider the logical data warehouse approach. Read more at: http://www.datavirtualizationblog.com/enterprise-data-warehouse-no-longer-suffice-data-driven-world/

To prepare for the General Data Protection Regulation, companies need to find a way to establish security controls over the entire infrastructure from a single point. Without investing in new hardware or re-building existing systems, data virtualization allows companies to quickly and easily comply with data protection regulations. There are three ways in which this can be done. First rule is not to replicate the data which will lead to governance and security nightmares. Second is that data virtualization makes it possible to apply consistent levels of security across the heterogeneous data sources which contains the data. Finally, data virtualization removes the need for replication and latency of updates of customer information, thus providing users accurate information as applied in the system of record. Thus, data virtualization can help in data protection. Read more at: http://www.datavirtualizationblog.com/3-steps-data-protection-compliance-gdpr/

Data Analytics has widespread impacts on not only commercial sectors but also healthcare. For example: First is by checking on hospital activities by maintaining relevant databases can help in finding inefficiencies in service provision and the overall costs of a healthcare facility can be reduced. Second is that data analysis also helps in allocating funds efficiently thus reducing the chances of embezzlement. Third is a database of patients’ records and medical histories can be maintained, which can provide a communication medium for the patient and every other individual working on that case. Also, if a healthcare facility is operated in multiple units, analytics can help ensure consistency across all facilities and specific departments. Lastly, storing staff data and keeping a check on their performance is important. Read more at: http://www.datasciencecentral.com/profiles/blogs/data-analytics-is-transforming-healthcare-systems

One can make an AI powered Chatbot in a very short period of time. You just need to figure out what problem you are going to solve with your bot, choose which platform your bot will live on (Facebook, Slack, etc.), set up a server to run your bot from, and choose which service you will use to build your bot.

Here are some of resources to get you started.

Platform Documentation:

1.Facebook Messenger Platform, 2.Telegram, 3.Discord , 4.Slack , 5.Kik etc.

Some third party Services can be used to build Chatbots. They are:

Mobile app analytics is used by professionals today to track their app. But there are flaws which needs to be fixed. One flaw is that the app focuses mostly on quantitative analysis and there are other general flaws. One must add quantitative analysis to the workflow in order to complete the picture. This analysis is further divided into heatmaps and user sessions recordings. Touch heatmaps gather all the gestures a user does in the screen and it also sees where the users are trying to interact. User session recordings enable to see what users are doing. Combination of qualitative and quantitative analysis has potential in terms of workflows and app optimization. Read more at: http://online-behavior.com/analytics/app-workflows

Competition today is much fiercer than competition in yesteryears. In such a world getting a comparative advantage of machine learning would be beneficial. Though in their initial phase data analytics and machine learning faced criticism, the development of data structures and more accessibility helped to minimize criticism. Data is the source of information and the mining right kind of data would lead to significant results. There are four elements of data management, namely hybrid data management, data governance, data science and data analytics. Linking all the departments of a company is necessary to ensure free flow of information and accessibility of data. Read more at: https://readwrite.com/2017/06/21/competitive-advantage-machine-learning-dl1/

Data is an important tool which manages a lot of important activities in the business. And this is further enhanced by artificial intelligence and machine learning and by ease of collecting and storing data. Managers rely too much on data for the guidance which abdicates their knowledge and experience. In a big data project the manager connects the internal and external team to collect and process the data in order to solve the problem. Data must be in usable form and the algorithms must identify statistically significant patterns. The results are then presented to the manager through different visualizations. The main problem is the managers are not good with data science and the scientists are not good with the businesses.  Read more at: https://hbr.org/2017/06/the-best-approach-to-decision-making-combines-data-and-managers-expertise

Data driven analytics is must for all business functions because of increasing complexity and market volatility. According to the survey of more than 300 executives in North America, U.K. and Ireland conducted by Dun & Bradstreet and Forbes Insights, 1.) Senior executives finally understand the value of analytics and are making investments in technology, people and processes. 2.)Data analytics skills gaps persist across the enterprise, as 27% of analytics professionals surveyed cite this skills gap as a major impediment in their data initiatives.  3.)Analytical methods and tools trail both the appetite and ambition of most business leaders. Analytics now drives today’s enterprise, from formation of business strategy to powering operational excellence. It has clearly moved from being an optional operational element to serving as the core of corporate activities. Read more at: https://www.entrepreneur.com/article/295522

Measuring the effect of quality on revenue and profits is one of the biggest challenges faced by digital publishers. It can be measured by measuring engagement of customers, i.e., their frequency of visits, how recent their last visit was, etc., which confirms the quality of the product. The next is that the publisher’s dilemma is balancing advertising revenue with audience revenue. Advertising revenue depends on quantity of audience impressions while audience revenue depends on quality of content. Also, more audience revenue requires higher quality user experience. As digital advertising revenue, particularly display ads, the need for greater audience revenue is very important. To measure success, the important data to capture are revenue by individual user. Using these data, the publisher can identify the combination of product attributes and price point, thus maximizing expected advertising revenue and audience revenue. Read more at: https://www.webanalyticsworld.net/2017/02/digital-publishers-analytics-dilemma.html#more-23565

To become a digital expert, customer experience should be put above everything and methodologies should be found to adjust to the continuously changing demands. The following are some ways to do so. The first is to become a top-notch expert with industrialized IT services, where quality should be improved and it should be ensured that the product line is aligned with business needs. The next is to modernize, during which architecture must be planned and implemented. The last stage is Optimize in which improvements are made. The second is switching to agile operations to achieve maximum efficiency. Third, is to create an engaging experience for the consumers by designing a unique omni-channel approach, analyzing real-time data, thus improving purchase journey. Lastly, opportunities for digital services must be availed. The end result is the delivery of a truly digital experience. Read more at: http://www.datasciencecentral.com/profiles/blogs/enterprise-journey-to-becoming-digital

Nowadays, finding a desired job is not easy, but with personal branding, one can find it easily. Personal branding is a term coined by Tom Peters, in his breakthrough article “ A Brand Called You”. Every person is unique in its own skills. There are a lot of reasons why understanding and building your own personal brand will help you achieve success in the future. Some of which are: 1.) Question yourself: Ask yourself  Who are you ? What are you? Once you start identifying the blocks that build your personality, you can find yourself standing out from the crowd. 2.)  Social media: In the  present era you need  not go out to search for a job. What you can do is maintain your social media. A lot of  business partners who are currently running their successful businesses had their first encounter with social media. Does anything get better than this? Read more at: https://www.entrepreneur.com/article/295522

Demand for credit is increasing in the cashless economy where there is rise of digital money. Various startups are emerging that allows the user to buy now and pay later. They are targeting those consumer segments of India that does not have access to a Credit Card. Banks take loads of paperwork and much more time while giving loan, whereas these startups determine credit worthiness through social media. Slicepay is targeting college students aged 18-26 who usually don’t have credit cards and this segment of people need small ticket loans which other banks don’t provide. Also, for the loans given, they believe that it won’t lead to debt crisis because i) Credit taken are in small amount. ii) Analysis is secured. Read more at: https://www.entrepreneur.com/article/295918

HR analytics is a key element in any company’s progress. The slow growth of HR analytics has been a great concern for companies. HR leaders can present analysis in a more impactful manner by using the LAMP framework. 

• Logic- with trends, the logic for the occurrence should also be explained.

• Analytics- provide important insights from data using tools and techniques.

• Measures- verified and accurate numbers should be used in analytics.

• Process- motivate decision makers to act on data insights using right communication channels.

One should search himself online and keep track of photos. There has been continuous warnings from the guidance counsellors. Research says that at the time of admissions the profiles of the students are checked by the institutes, which might lead to the revoke of admission. One also shouldn’t post false information about the wrongdoings. Posting forbidden information online is considered illegal as it may violate institutions rule. It should also be made sure that the information entered by the individual is appropriate about name, email address, etc. these information must not be made to look unprofessional in any manner. Also others should be treated nicely on the social media including comments and trolls. Read more at: https://mobile.nytimes.com/aponline/2017/06/19/us/ap-us-college-admissions-social-media-tips.html?rref=collection%2Ftimestopic%2FSocial%20Media&action=click&contentCollection=timestopics&region=stream&module=stream_unit&version=latest&contentPlacement=7&pgtype=collection&referer=https://www.nytimes.com/topic/subject/social-media

In describing the key traits that a successful business man possesses, one cannot say who is the best. Just to get the idea while using IBM's supercomputer Watson, online career management website "paysa" analyzed the speeches, essays, books and interview transcripts of today's most powerful leaders. So to do this, it surveyed 8 industries. And in majority of these , Watson discovered "intellect" was the top personality trait for leaders. It also identified other traits, i.e. imagination, cautiousness, assertiveness, adventurous and more. Elon musk scored the highest score for the "most cautious leader". Above all, Bezos, Cook and Meg Whitman each tied for "most altruistic leader" at 98 percent. Whitman also topped the list for the most "achievement-seeking leader." Mark Zuckerberg seemed to exhibit the least amount of top common success traits identified by Watson. Although that doesn't mean much -- the Facebook co-founder and CEO just has his own set of unique traits that make him stand out. Read more at: https://www.entrepreneur.com/article/295452 and  

https://www.paysa.com/blog/2017/05/24/watson-personality-analysis-by-industry/

Data can be put to use in many ways and it should be explored. Data should be used to its full potential, this is not about technology but management. A team of data scientists employ a series of various analysis to look into the entire series from data insight to profit. There are 7 methods to put data into work. 1) Use data to make better decisions along the chart. 2) Use innovations in products, services and processes. 3) Making existing products more valuable. 4) Improve quality, eliminate costs and build trust. 5) Sell or license richer data. 6) Asymmetries should be exploited. 7) Connect providers and those who need the data. These help to provide greater value to others. Read more at: https://hbr.org/2017/06/does-your-company-know-what-to-do-with-all-its-data

The present business environment is volatile and full of uncertainties. Therefore, a need arises to improve efficiency and profitability. Though many organizations rely on traditional techniques, predictive analytics is the new trend of managing risks and monitoring frauds which eliminates all the guesswork. Predictive analytics help us in reaching the source of fraudulent transactions and in dealing with future plausible attacks. Lack of corporate transparency and missing public trust should be dealt with by using advanced tools for managing huge data and ensuring accountability. Predictive analytics helps in building the customer profile to know his credibility which is useful for banks. Read more at : https://blogs.metricstream.com/ready-predictive-analytics-revolution/

Big data has now become old, organizations are very well familiar with it. But some of them are still struggling with data. Data lakes provides easy access of data and data mining. Due to management defaults data may turn into data swamps making analysis difficult. Data Lake has a lot of benefits, but the data growing in size becomes difficult to handle. To avoid this problem following steps are taken at the time of creation. 1) Too much data must not be collected at the beginning. 2) Data insighting cannot be done manually, so machine-learning capabilities should be enabled. 3) Businesses should keep an eye on changing data statistics and the employed models. To make it successful one needs to integrate it with business strategy and outcome. Read more at: https://www.readitquik.com/articles/elastic-computing/smart-ways-to-manage-your-big-data/

SecondMuse, place of work that collaborates with organizations to assist solve complicated issues, looked to the most recent drone and 360 video technologies to assist showcase cultivation — the farming of aquatic life-forms — in United Republic of Tanzania.

Led by the Australian Department of Foreign Affairs and Trade’s InnovationXchange, in partnership with SecondMuse, the goal was to award comes that each facilitate scale back environmental impact and increase property.

Ben Kreimer, a drone and computer game individual, and Brett Garling, producer and founding father of Cut Canvas inventive, shot 360 video underwater, on land, and within the air to document 3 of those initiatives.

More than seventieth of Tanzanian alga farmers square measure ladies, and rising ocean temperatures square measure reducing the economic viability of alga farming, per the Blue Economy Challenge web site.Read more at : http://blogs.discovermagazine.com/d-brief/2017/06/08/drones-showcase-aquaculture-in-tanzania/#.WUK_3BN968V