The most ambitious project of India, Aadhaar project relies completely on Big Data. From collection of data to storage and utilization of biometric information of the entire population, big data till date has crossed over the billion mark. It is needless to say, a project of such a vast magnitude must be plagued with ample challenges but as its powered by big data, the chances of success is high.
Basically, Aadhaar is a unique 12 digit number assigned by the UIDA, Unique Identification Authority of India to an individual residing in India. The project was launched in the year 2009 under the supreme guidance of former Infosys CEO and co-founder Nandan Nilekani. He was the sole architect of this grand project, which required several added inputs from various other sources.
MapR, a business software company headquartered in California is providing technology support for the most-ambitious Aadhaar project. It is the developer-cum-distributer of “Apache APA +0.00% Hadoop” and for quite some time it is optimizing its well-integrated web-scale enterprise storage and real-time database tech for this project.
The encompassing technology architecture behind Aadhaar is structured on the principles of openness, strong security, linear scalability and vendor neutrality. The system is expected to expand with every new enrollment, which means it’s required to handle millions of transactions through billions of records, each day.
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Things are not at all going right in the technological sphere. The domain is shrouded under the dark haze of WannaCry Ransomware this weekend. After the relaxing weekend, the Monday morning situation could never have been worse. The figures revealed on Monday evening by the Elliptic, a Bitcoin forensics firm, affirmed with the duty of keeping a close watch, confirmed a digit of $57,282, 23 shelled out to the hackers of Ransomware malware attack, who took over innumerable amount of computers worldwide on Friday and over the weekend.
The recent past has been witnessing the unprecedented malware attack across 150 countries. The current picture describes more than 200000 systems around the world being affected and the loss of tons of data.
Also read: How To Stop Big Data Projects From Failing?
A few years back also, Ransomware was unheard of and today it has emerged as one of the major issues of concern. So, what is the solution now? Several veteran data scientists and the honchos of the technological world have voted for Predictive Analysis as the ultimate solution for destroying Ransomware.
With the conventional cyber defense mechanisms at a backseat, Predictive Analysis defense technology remains the ultimate resort for any organization. The Predictive Analysis is mainly dependent on instituting a pattern of life within the enterprise and saving from disgruntling malware and similar disturbing activities.
Paul Brady, the CEO of Unitrends, explained the procedure where the backup system uses the tools of machine learning to identify and understand that certain data anomalies indicate the threat of a Ransomware attack.
So the above mentioned description clearly depicts the many advantages of Predictive Analysis. Now, the sad part of the story remains, that the difficulty in management remains the major blockage for the employment of this method. Let’s hope for the best and wait for the day when Predictive Analysis would be the only possible solution. Till then gather information on SAS predictive modeling training in Pune and Gurgaon only at www.dexlabanalytics.com
Do you know why several organizations face problems while implementing Big Data? Still wondering? The reason is lack of poor or non-existent data management strategies.
Proper technology systems need to be adopted. Without procedural flows, data is impossible to be analysed or delivered appropriately. However, before we delve deeper into making a plan to introduce data management strategies into the business, we should pay enough attention to the systems and technologies we are thinking to launch, along with the number of improvements to be made.
Big Data is ruling the tech world. Here are few types of tech that needs to be a part of a successful data management strategy:
Common data mining tools are R, SAS and KXEN.
More consistent, Automated ETL is used to extract, transform and load data.
They are efficient in offering a protective layer of security and quality assurance by doing a proper problem diagnosis and monitoring critical environments.
BI and Reporting Analytics
Turn data into insights, with BI and Reporting Analytics. It is very vital that data go to the right people and of course in the right manner. If that doesn’t happen, organizations suffer incessantly.
Analytics is a huge branch of study, starting from customer acquisition data, tracking details to intriguing user-friendly interfaces and product life cycle.
For More Details, Read The Full Blog Here:
Understanding The Core Components of Data Management
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