SigmaWay Blog

Both the IT giants, Google and Apple have revamped their business model which ensures that you get more money for each downloaded app by the consumers. According to reports, both Google and Apple have been internally testing out the viability of this process. For iOS developers, their share will be only paid after a consumer has been subscribed for more than a year. Google on the other hand, is flexible and lenient enough to release the money in the direction of Android developers right away. Android is the most popular mobile platform in developing countries, primarily due to its availability of affordable devices. While iOS have kept its sanctity with stringent app certification norms, Android has flourished with its open-source approach that comes with its own caveats. Read more at: http://www.tgdaily.com/mobile/160751-app-developers-can-expect-more-money-from-google-and-apple

While developing data strategies in the future, organizations must consider these new emerging trends: 1) Data's center of gravity is moving more to the cloud day by day, which means one should be looking to keep all their data tools for processing to analytics in the cloud. 2) Hybrid data technologies are critical to the cloud system and hybrid data systems like SQL Server, MySQL, etc. is predicted to become the norm by 2018. 3) With new tools for data analysis being innovated, businesses need to connect to many data sources that span across databases, Hadoop ecosystems, and web applications. Read more at: http://data-informed.com/how-to-capitalize-on-the-data-landscape-of-tomorrow/

Big data storage is not a tough task to current organizational context. There could be n number of big data on different aspects of a company, but storing will not serve the purpose. Analysis and implementation are the most necessary part in any business. So that means it requires specialized personnel and a processing tools and techniques which can leverage these data into predictive modelling. But in the current context only 23% of total industrial scenario can have that resource to successfully implement. Most of the cases the organizational legacy system takes too long, time to process these data and becomes non contextual in the business sector.

To read, follow: http://www.cio.com/article/3075423/it-strategy/it-wants-but-struggles-to-operationalize-big-data.html

Social presence and cyber security issues have a deeper correlation regarding security breaching. Even a normal post can harm any damage by sending a phishing mail. You can be at home, work, on your phone, with a tablet or on a public computer or borrowed device. Your phone, which doubles as a virtual office, is the easiest channel for data to leak out. Data leaks can happen in a harmless post about relocating for work when that news is still confidential to your company. It can happen if you hit "paste" with text from a work-related email in your clipboard and post it into the wrong window on your screen and it can also happen if your smartphone auto-corrects something you spelled wrong in a social media post to some project code name that you just used in an email. So an unimportant activity can create a huge impact.

To read, follow: https://www.entrepreneur.com/article/272459

Any organization is hugely dependent on data. Either these data are raw in nature or coders has full authority to cluster and filter them. But the process of critical analysis of such data is not simple. So highly skilled data scientists are required, but unfortunately these job demands high specialization and its platform is not yet developed.

Read more at: http://www.pcworld.com/article/3067957/how-the-skills-shortage-is-transforming-big-data.html

Currently one of the state of the art algorithms in Machine Learning is Gradient Boosting Machine (GBM). GBM can be used for regression, based on decision trees as prediction models. In GBMs, the learning procedure consecutively fits new models to provide a more accurate estimate of the response variable. The principle idea behind this algorithm is to construct the new base-learners to be maximally correlated with the negative gradient of the loss function, associated with the whole ensemble. The loss functions applied can be arbitrary, but to give a better perception, if the error function is the classic squared-error loss, the learning procedure would result in consecutive error-fitting. Read more at: http://www.dataminingblog.com/

NASA has revealed that it is going to fund for futuristic space technologies. There are eight projects which are part of the Innovative Advanced Concepts Program. There are various phases and aspects of the project. Out of the many revolutionary things in this project is that, engineers are developing an aircraft which can stay aloft for a long time. If this project is a success, it will be a great leap for mankind. Check out the article to know about the other parts of the project: http://www.dailymail.co.uk/sciencetech/article-3589538/From-Magnetoshells-humans-Mars-growable-habitats-Nasa-reveals-funding-futuristic-space-technology.html

As a result of increased e-commerce in B2B and the general availability of data on the Internet, B2B pricing and product information is easier to find. Buyers have more information than before to have relevant and convenient product and pricing. To meet these assumptions, B2B companies are leveraging advanced analytics. Analytics can help companies to customize buying experiences through commerce channels. It also provides sales reps about what customers are likely to purchase and what prices make sense to quote in the context of the deal. Read more at : http://data-informed.com/how-advanced-analytics-is-changing-b2b-buyer-expectations/

Precision analytics is enabling e-commerce dealers to deliver goods fast after getting an order. They study buying patterns and prompt the buyer even before they decide to click. India's largest mobile wallet, Paytm is also trying to strengthen its presence in e-commerce. E-commerce company Amazon also use predictive analysis to study customer buying trends. Read more at: http://www.business-standard.com/article/companies/precision-tool-to-get-speed-on-e-commerce-profit-road-116051600057_1.html#

Big data & analytics bring together open source technologies. That works together to accelerate the data pipeline. They are : Spark - for large-scale data processing

Mesos -  for cluster resource management

Akka - for data-heavy applications

Cassandra - for storage engine and 

Kafka - for event processing

We have all heard about helicopter parents, but did you know that you can actually be a helicopter pet owner? Yes, you can actually keep a track of your pets and monitor them from work. When you miss your pet and you are worried about him, there are gadgets to make this possible and easier for you to talk with your pet. Pet lovers will totally love this bit of news as they cannot just play remotely with their pets but also monitor their health. Check out the whole article below: http://www.wsj.com/articles/gadgets-for-playing-with-your-pet-remotely-1455223286

Visual content is more effective and interesting than text article. In a research, it was found that colored and eye-catching visuals increase people's willingness to read a piece of content by 80% and 40% of people respond better to visual information than plain text. Infographics and videos are also powerful, and interesting platform to represent a message. Research shows that infographics are liked and shared 3 times more than other any other content on social media. Read more at: http://www.business2community.com/content-marketing/20-infographic-video-facts-feel-power-visual-content-01544708#Cr0SLgpyZOmoqY49.97

With regards to big data analytics in the healthcare industry, there's a noteworthy contrast between beginning an activity and succeeding with it.  We have to collect data systematically. Organizations should also conduct regular reviews of their data integrity and health information management programs to help clinicians to collect important data in a standardized, and accurate manner. Big data analytics is costly and hiring an outsider with more experience might be interesting for suppliers who are feeling lost. Outsourcing can also be risky when it comes to data security. Read more at: http://healthitanalytics.com/news/how-to-build-a-successful-big-data-analytics-program-in-healthcare

Predictive analytics incorporate an assortment of measurable strategies from predictive modelling, machine learning and data mining that investigate present and chronicled certainties to make forecasts about the future. There are numerous components that show churn: drops in item utilization, debasing assessment in client communications. But the issue is predictive analytics depend on complex models that consider numerous "variables" that could possibly be independent. Key steps that can make client progress with prescient examination: 1. Quit attempting to rethink the whole. 2. Understand that it is just an expectation, not an assurance. 3. Move from imagining a scenario where to what's next. 4. Make it an agreeable, shut learning circle. For more read: http://www.cmswire.com/analytics/leveraging-the-power-of-predictive-analytics-to-control-churn/

The advanced age is loaded with examinations, estimations and learnings. It has brought streaming information in real time. In today's predictive analytics world, advertisers can see the future effect before spending a dime. Advertisers can hope to know how likely it is for a specific occasion to happen in the life of a customer. Customers are focused on forecasts, which depends on their computerized impression. For more read: http://www.cmswire.com/analytics/predictive-analytics-makes-marketing-dollars-work-harder/

The term big data are applied to data sets which is beyond the ability of traditional databases to capture, manage, and process the data with low-latency. Big data analytics can be real-time processing or streaming analytics. The primary goal is to help businesses to use data to be well informed about their customers, decisions they should be making, improving efficiency and various other use cases. For more read: http://www.cbronline.com/news/big-data/analytics/big-data-analytics-what-it-is-and-why-you-should-care-4894627

Phone analytics are used for understanding of what happens with customers on the phone. It is possible to get an overview of all the call activity within a certain timeframe. Phone calls are an important part of marketing campaigns, particularly for the business-to-business market. But, without call-tracking data, there's no way to know how well the sales team is doing with those follow-up calls. Using the analytics data, businesses can take steps to improve by reducing the call abandonment rate.  For more read: https://www.entrepreneur.com/article/273584

Having access to information doesn't mean consumers will correctly understand and interpret the data. Real estate entrepreneurs also must gain a better understanding of this data to make it useful for customers. Real estate leaders should have knowledge of something when they use predictive analytics i.e. 1. Fortify the foundation, 2. Draw up a blueprint, and                                                                                                              3. Entertain your guests.    For more read: https://www.entrepreneur.com/article/275805

By utilizing technology & traditional data analysis, wholesalers can use predictive analytics: 1. Forecast future customer needs, 2. Discover trends to foresee future business scenarios, 3. Predict changes in customer segments and the impact to the organization,  4.develop future pricing strategies, 5.improve upcoming marketing campaigns, 6.project customer profitability, 7.develop strategies to maintain customers, 8. evaluate their exposure and risk profile, 9. identifies potential new customers, markets and segments. By leveraging the use of predictive analytics, wholesalers can gain the upper hand over competitors in today's digital economy. For more read: target=_blankhttp://clarkstonconsulting.com/blog/wholesale-distribution-and-the-digital-economy-the-importance-of-predictive-analytics/

Predictive modeling drives Account Based Marketing or ABM strategies by identifying the right audiences. With a good ABM strategy, you can personalize your website messaging to individuals once they land on your pages.  Personalization software tracks visitor sources and actions. Then uses behavioral, demographic data to provide personalized experiences according to the visitor's characteristics. Technology won't do everything. Successful ABM strategies depend on proper integration between sales and marketing. For more read: http://customerthink.com/whats-missing-from-your-account-based-marketing-strategy/