Data Minimization in the age of Big Data!

In the age of Big Data where every second feeds tonnes of data to the cloud, there is an information overload happening. Do you really require to collect all that data and store it in the hope that you will use it someday? This is where Data Minimization comes into the picture.

As businesses grow, so does the amount of data/information that it collects over the years. Faced with the challenges of storing and managing Big Data, many are realizing that storing everything is not only unviable, but also unnecessary.

Don’t get buried under the Big Data deluge. Get in touch with Sysfore’s cloud specialists and we’ll help manage your information storage through Data Minimization.

Businesses have invested millions of dollars into storage infrastructure so that they can capture every bit of available data. But as their datasets have grown, many have realized that they simply do not need much of the low level data created. More importantly, they have discovered that much of that data will never be used.

Whether they use in-house data centers or cloud archiving options, there is a cost associated to all of this unnecessary information that they hold.

What is Data Minimization?

Data minimization refers to the practice of limiting the collection of personal information to that which is directly relevant and necessary to accomplish a specified purpose.

Data Minimization - Minimizing Big Data

The deluge of information started as companies and organizations began to understand the power of data. As data becomes more ubiquitous and easy to collect, analysts are faced with a hurricane of potential data points. The impulse was to save all of it – indefinitely.

As the Internet of Things continues to grow, organizations are faced with more ways to collect data, including and especially private, personally identifiable data.

The focus needs to shift towards data minimization, where data is prioritized and unnecessary data is discarded. Instead of a “save everything” approach, data managers are now embracing a data minimization policy, keeping only what’s relevant and necessary. Even Walmart only relies on the previous 4 weeks of data for its day-to-day merchandising strategies.

Underlying Data Minimization benefits

One factor which is becoming increasingly popular among organizations is the cost and time factor involved in hoarding this excessive data indefinitely. All data storage costs money, and no business has an infinite budget to go on collecting and storing data indefinitely.

Another factor is the corporate computer security. Having too much data like personally identifiable data brings big risks. There is the risk of data loss and security breaches. A major leak of sensitive personal information can easily destroy a business or even lead to charges of criminal negligence.

Data Minimization mitigate both these factors significantly. It avoids multiple ways of storing data, thus reduces the cost of storing indefinite chunks of information. The value of the stored data decreases quickly and imagine the loss of a piece of information which is not even compatible now.

The idea of Data Minimization is going strong and it is only a matter of time these are included as standard procedures for mitigating risks.

Sysfore can guide you towards a Data Minimization approach for your businesses. For more information, you contact us at or call us at +91-80-4110-5555.

Microsoft Build Developer Event 2016 – Azure Makes IoT Even Easier for Businesses

Build 2016

Adds Azure IoT Gateway SDK and Device Management to Azure IoT Hub

Microsoft held their annual developer conference called Build out in San Francisco. The three-day event from March 31 to April 1, had various Microsoft executives detailing and demonstrating the vision for computing. There were hundreds of mini-seminars on Windows development detailing what is new.

At Build 2016, Scott Guthrie, executive vice president of the Cloud and Enterprise Group, and Qi Lu, executive vice president of the Applications and Services Group, demonstrated how Microsoft Azure services and the Office platform can empower developers to easily leverage advanced analytics, machine learning, emerging cloud development models and the Internet of Things (IoT) to build their intelligent apps.

Azure Internet of Things (IoT) gets a boost

Two new offerings were announced that make it significantly easier for customers to manage their IoT deployments: Azure IoT Hub device management and the Azure IoT Gateway SDK. The preview of these powerful new capabilities, shows Microsoft’s support for providing developers, IT managers and OT operators with tools to make managing their IoT deployments easier than ever.

Drop by Sysfore Technologies, to get the latest information on the Azure IoT Hub device management and the Azure IoT Gateway SDK.

The diverse Internet of Things (IoT) environment is mixed with many types of devices with different software, firmware, connectivity and security capabilities dispersed geographically . For many businesses, it’s a challenge to keep the software, firmware and configuration of new devices up to date.

They also need to connect to older or legacy devices to communicate directly with the cloud. The new offerings address these challenges and continues to simplify IoT, so customers can focus on development instead of the logistics.

Azure IoT Hub device management

The device management feature in Azure IoT Hub allows enterprises to remotely maintain, interact with, and manage IoT devices at scale from the cloud using accepted open source standards. Administrators can enroll, view status and health, organize, control access, and update the software, firmware and configurations of millions of geographically dispersed IoT devices.

Customers can now realize significant time and resource savings by removing the burden of developing and maintaining custom device management solutions.

Azure IoT Hub scales to manage millions of devices supporting the LWM2M protocol, the leading standard from the Open Mobile Alliance (OMA) for IoT device management. The IoT Hub device management enables a simplified cloud programming model for IoT solutions through new service side APIs:

  • Device Registry Manager API:Provides a first-class device object for working with IoT devices in your cloud solution. Through this device object, your cloud solution can interact with device and service properties, which is used by the device for configuration or to inform the IoT solution of device state (e.g. firmware version, OEM name), service properties, such as tags etc.
  • Device Groups API:Work with your fleet of devices in groups and control access in a way that maps to your solution topology.
  • Device Queries API:Find devices in your IoT solution based on tags, device, or service properties.
  • Device Models API:Define the information model for the devices and entities in your IoT solution.
  • Device Jobs API:Run and monitor simultaneous device orchestrations on your global fleet of devices across a heterogeneous device population.

Azure IoT Gateway SDK

The Azure IoT Gateway SDK enables businesses to connect legacy devices and sensors to the Azure cloud without having to replace existing infrastructure. And for developers, the SDK helps to easily build and deploy “edge intelligence” modules that optimize and process data before it’s sent to the cloud, allowing your business to benefit from minimized latency, reduced bandwidth costs, and more effective enforcement of security and privacy constraints.

The Azure IoT Gateway SDK achieves this by providing source code that takes care of much of the necessary busy work required for the development of a gateway application, including dynamic module loading, configuration, and data pipelining.

Get the latest information on the Azure IoT Hub device management and the Azure IoT Gateway SDK from our IoT specialists. Mail us at or call us at +91-80-4110-5555 to leverage the new updates using Sysfore’s IOT Suite.


Data Lake – Is it the future for Big Data?

Data Lake is a new storage concept that is gaining ground in the Cloud. Often the Data Lake term is being used as part of the Big Data solution. In theory, it is where you can store raw data in its native format, usually in Hadoop and Hadoop Distributed File System (HDFS). It can be used and processed to create data sets for other applications and users as and when needed. You don’t worry about the complex (and often expensive) data pipeline needed to simply collect and store diverse data.

The credit for coining the term Data Lake goes to James Dixon, Pentaho Chief Technology Officer. Dixon used the term initially to contrast with “data mart”, which is a smaller repository of interesting attributes extracted from the raw data.

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