Big Data

Personal Data – Tracked and Mined By Mobile Apps

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While malware still remains to be a major concern for mobile devices a new study suggests that there are more severe threats lurking within your mobile apps. Data mining via intrusive mobile apps has become a topic of debate. There are a number of mobile apps that exhibit risky behavior when it comes to sharing personal information – that includes accessing user’s contacts, calendars, locations and more. The unwarranted data mining from apps is more of a threat to users than any malware. So, why should we care if any of the (seemingly innocent) app can access your contact list or look at your purchase history?

You should care because this unprotected flow of user data over unprotected networks could mean that more than just marketing companies are sniffing around for your personal info.

Have you ever wondered why a flashlight app might need your location, calendar or address book? In general, apps are collecting more information than required. This information may not always be created securely and may become the target for criminals and illegal activities.

Major risks that enterprises need to be aware of:

  • With the emerging trend of BYOD (Bring Your Own Devices), the problem of data mining is becoming even more important.
  • Enterprises need to be more careful when it comes to mobile device management.
  • Adequate security features can ensure that sensitive information does not get into wrong hands.
  • Strong passwords, network encryption and limiting the types of apps that can be downloaded on devices are some key measures to be implemented.

Above all, it is important to remember that data always flows two ways and it is important to keep your professional data separate from your private data. Never leave your devices open and be careful what you download on your mobile devices!

Artificial Intelligence

Machine Learning – Future of Data analytics

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Have you ever thought of how a machine can learn? I find it fascinating that today you can set rules and certainly provide enough historical data to a computer, which will get it trained to do a specific task. Based on the rules and thesis data, the machine can be programmed to learn how to do tasks so that we humans have no way of knowing what steps it is explicitly subscribing to get the job done. It is like the brain, you can not cut open and understand the inner workings.

Machine Learning – Future of Data analytics


Machine learning is a scientific discipline that addresses the question “How can we program systems to learn and automatically improve with experience?” Learning in this context is not learning by heart, but recognizing Complex models and make intelligent data-based decisions.

Rather than creating code, we become trainers. Computers learn. It is called machine learning.

What has enabled Machine Learning to reach this point of inflection at the present time? Three things:

  1. We now have better algorithms.
  2. The drastic explosion of computing power.
  3. We, as human beings, have accumulated a great deal of data that machines can learn.

Benefits of Machine learning

Machine learning offers intelligent alternatives to the analysis of huge volumes of data. By developing fast and efficient algorithms and data-driven models for real-time processing of data, machine learning is able to produce accurate results and analytics.

How Gmail can sort your stuff and classify it into primary mail, updates, promotions, and social.

It is not the task of a human being, nor even a massive team – to update hundreds of stories every minute.


One could conclude that machine learning is the new avatar of Big data analysis. I did not know that simple regression/adjustment was part of machine learning and an essential element! In my opinion, anyone who deals with any type of data must take this course, just for the sake of it. You will certainly learn something useful.

At Verve Systems, we can help you with machine learning specialized in the IoT application, the ML is the main method among these computer applications in IoT. This kind of applications is fairly common these days, such as Google Maps and other GPS in the car system. The IoT application includes utilities, manufacturing, healthcare, insurance, retail, transportation and most of these applications require ML algorithms to translate the data into something easy to see.

Have a closer look at its opportunities:

Big Data

Trends and Technology adoption in Dairy Industry

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In the dairy industry, since the last couple of years, there has been a significant rise in the overall consumption of dairy products starting from milk, cheese to yogurt. Among these products, milk is observed to be consumed as single content in the form of a beverage or as an ingredient.

Trends and Technology adoption in Dairy Industry

Additionally, consumers are becoming health conscious and so they prefer convenient options that can be part of their daily routine. Therefore it is very integral for the industry to produce dairy products that deliver for these needs.

Some of the emerging trends shaping the future of the dairy industry are:

  • Industry collaboration
  • Digitization for product innovation
  • Upgradation in global economics
  • Implementation of advanced manufacturing processes and technologies
  • Consumer demands for health-conscious products

The future of the dairy industry depends on how well it manages the upcoming opportunities and risks arising from the key drivers. A wise step would be the incorporation of digital technologies to boost the overall process. What can be expected as a result when IT is penetrated in the dairy industry.

Digitization for product innovation:

  • The emerging digital era holds great promise for the dairy industry.
  • Digital technologies help identify gaps in existing products, develop new and innovative ways of product usage and packaging and pave the way for venturing into newer markets.
  • Using Big Data and analytics, companies can perform real-time sales analysis to understand consumption patterns, which can help modify production and marketing strategies.
  • Mobility solutions can help dairy players to improve the customer experience by providing a real-time connection between the companies and the consumers.

The progress in dairy products has remained steady even with the challenges in economic conditions. Further, growth opportunities seem promising too, especially in South Africa with a slight improvement in economic conditions.

An increased focus on industry digitization is expected with an objective to achieve considerable growth. Once the desired level is attained regarding demand in the market, dairy companies should aggressively look to scale up production through inorganic growth and jump into fresh demand.

Big Data

How wearables and data analytics can boost patient health?

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The arrival of wearables is increasingly becoming significant for any of the pharma requisitions. Everybody can say this is my data and this is my question. The insights, analytics, and visualizations help to boost patient health, improve outcomes, streamline manual processes and facilitate exploration of newer avenues in medical research and epidemiology.

How wearables and data analytics can boost patient health

1. Wearables can be employed for monitoring and gathering vital data pertaining to patients in real-time as well as historic modes.

2. Cardiac health can be monitored by making the patient use wearable which will continuously collect and transmit data for comprehensive analysis in and off the clinic.

3. Data from diverse segments of wearers can be aggregated for carrying out epidemiological studies. Healthcare analysts can classify the data based on demographic, geographic and activity level-wise considerations which would provide analytical insights.

4. Wearable devices can be coupled with smartphones with inbuilt GPS for transmitting coordinates and relevant data to the nearest clinic when an emergency arises.

5. Surgeons putting on smart glasses can keep track of the patient’s vital symptoms and critical medical apparatus in real-time while the operation is underway.

Patients with a proven history of a particular ailment can be alerted when the symptoms become severe to manage. For example, the intelligent platform can collect and analyze the vital signs of the patient with a cardiac problem and can decisively tell if the heart rate surge is because of exercise or aggravation of heart ailment calling for immediate medical intervention.

Cost Factor
The patient’s health can be mapped comprehensively with the aid of wearable devices. This helps curb healthcare costs as doctors can suggest remedial measures beforehand. Doctors can address concerns prior to the landing of the patients in the emergency room. The holistic information offered also helps doctors motivate patients, especially with chronic illnesses, better and convince them about taking preventive measures all along. Easily understandable data generated by wearable analytics also compel patients to be circumspect of potential consequences that can surface if they don’t’ pay attention to doctor’s advice. Medical costs can be slashed as patients become more engaged and doctors get accurate information in real-time.

Medical insurance providers will be able to adjust the insurance terms and future premiums based on the patient’s current rate of recovery and the degree of deviation.

Medical practitioners would be able to fully leverage the limitless potential of wearable technology keeping in perspective the fact that the platform will be completely compatible with cost-competitive systems. This would also enable the apps to run directly.