Big data is the new CRAZE. Reports suggest that investments in big data have surpassed $57 billion in 2017, and are expected to rise by 10% for the next three years.
Customers are happy – those who have applied advanced capabilities to predictive analytics, machine learning, customer analytics, customer profiles, inventory management and tracking, and more – as big data implementation across many verticals has resulted in measurable positive results.
Big data is showering its miraculous effects on a range of industries. And the healthcare industry is not left out of the bandwagon. Precision medicine is at the brink of a revolution in individualizing treatment, and healthcare professionals are devising ways to prevent and treat diseases with granularity down to a single patient’s genome. Nevertheless, many out there shudders thinking if such humongous amounts of personal data stored in servers becomes vulnerable to threats from attackers. What will happen then?
It is expected the global precision medicine market will hit $88.64 billion – FYI, precision market is a specialized domain that includes data on a patient’s genes, lifestyle and environment to draw a clear picture of his/her health.
Numerous efforts are being implemented to secure the storage facilities in which large chunks of genetic information are stored. Last year, a leading cyber-security company, Northrop Grumman Corp. published a white paper penning down clear guidelines about how to secure precision medicine data. The company seeks out to aid the National Institute of Standards and Technology and the White House Precision Medicine Initiative.
To this, the AHA’s Institute for Precision Cardiovascular Medicine developed the Precision Medicine Platform to boost research and treatment of this particular kind of treatment. The platform is rich in functions, including high-end analytic tools that enable advanced computing and sharing of clinical trial data, hospital data, pharmaceutical data and personal data. The security build-up in here is very strong, and it passes through all crucial compliance tests, according to Laura Stevens, AHA data scientist – “Even if you have data that you’d like to use, it’s sort of a walled garden behind your data so that it’s not accessible to people that don’t have access to the data, and it’s also HIPPA compliant. It meets the utmost secure standards of healthcare today,” she explained.
The National Institutes of Health is creating a database to store genetic information to facilitate researchers in curing and preventing cancer and other diseases. It aims to collect data from around 1 million Americans. For applying data on a larger, more diverse population range, genetic information should be collected from larger demographics – that’s more feasible.
The AHA’s Myresearchlegacy.org invites individuals to donate their health, genetic and lifestyle data to aid researchers in treating patients. At present, the researchers are busy conducting precision medicine studies on treating diseases, like pancreatic, breast and other types of cancers. Not much development would have been possible without the advancement in computing power and storage coupled with big data and AI.
“The combination of benefits from process optimization, the ongoing transformation of medical data collection along the analog to digital continuum, and the availability of cheap memory and processing power and coding talent make the evolution of precision medicine inevitable,” David Sable, who runs the Special Situations Life Sciences Fund wrote in Forbes. Apart from managing the fund, he teaches entrepreneurship in biotechnology at Columbia University.
For always, the platform services, like clusters with Apache Spark big data framework, Amazon Elastic MapReduce and EMR thrives to pump up aggregation and analytics. Sometimes, where AI and machine learning tends to be time-consuming, EMR clusters work like a miracle in scaling and making the entire set of things faster to implement, thereby answering research questions faster and identifying crucial insights related to healthcare.
For in-depth understanding on Apache Spark, get certified in Apache Spark Training by DexLab Analytics. They are a prime Apache Spark Training institute in India.
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5G stands for fifth generation wireless connectivity based on the IEEE 802.11ac standard of broadband technology, though an official standard is yet to be fixed. It comes with a lot of promises – better bandwidth, faster speed and lower latency that affects (positively) customers and businesses, as well.
Although it isn’t expected to roll out until 2020, a large number of companies have already started prepping up to adopt and incorporate 5G mobile connectivity into their business scopes and operations. As the biggest shift in technology is looming right ahead, business leaders around the world are leaving no stone unturned to fathom the rich impact of 5G on several next-gen techs, like self-driving cars and cloud computing.
A substantial part of the Apache project, Hadoop is an open source, Java-based programming software framework that is used for storing data and running applications on different clusters of commodity hardware. Be it any kind of data, Hadoop acts as a massive storage unit backed by gargantuan processing power and an ability to tackle virtually countless tasks and jobs, simultaneously.
In this blogpost, we are going to discuss top 10 Hadoop interview questions – cracking these questions may help you bag the sexiest job of this decade.
There are 3 layers in Hadoop and they are as follows:
Hadoop distribution includes a generic application programming interface for drawing MapReduce jobs in programming languages like Ruby, Python, Perl, etc. and this is known as Hadoop streaming.
Begin by clicking on stop-all.sh and then on start-all.sh
OR
Write sudo hdfs (then press enter), su-hdfs (then press enter), /etc/init.d/ha (then press enter) and finally /etc/init.d/Hadoop-0.20-name node start (then press enter).
Use multiple nodes and the distcp command to ensure smooth copying of files between HDFS clusters.
In case, a node executes a task slower, the master node has the ability to start the same task on another node. As a result, the task that finishes off first will be accepted and the other one will be rejected. This entire procedure is known as “speculative execution”.
Here, WAL stands for “Write Ahead Log (WAL)”, which is a file located in every Region Server across the distributed environment. It is mostly used to recover data sets in case of mishaps.
FSCK command is your to-go option to do file system check in HDFS. This command is extensively used to block locations or names or check overall health of any files.
Follow
hdfs fsck /dir/hadoop-test -files -blocks –locations
A block divides the data, physically without taking into account the logical equations. This signifies you can posses a record that originated in one block and stretches over to another. On the other hand, InputSplit includes the logical boundaries of records, which are crucial too.
The article has been sourced from – www.besthadooptraining.in/blog/top-100-hadoop-interview-questions
Learn how Big Data Hadoop can help you manage your business data decisions from DexLab Analytics. We are a leading Big Data Hadoop training institute in Delhi NCR region offering industry standard big data related courses for data-aspiring candidates.
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Flipkart is strengthening its base in the field of Artificial Intelligence, and so far, this year has been treating them well. After pegging fresh influx of funds, appointing a new CEO at the helm of affairs and reportedly thwarting its tailing rival, Amazon in September, Flipkart is all set to enter the most promising arena of artificial intelligence and machine learning, NOW.
In an interview to a leading daily journal, Sachin Bansal, the notable co-founder and Chairman of Flipkart is found saying – “we ready to invest hundreds of millions of dollars” in the AI gambit over the next few years. “This is the next big thing for us, where we are betting big on the use of AI and machine learning to solve problems at Flipkart. India’s problems are unique and we need to apply AI in the ecosystem to solve Indian problems. We believe that some of the focus areas for AI in developed countries cannot be applied for India. At Flipkart, we will solve problems differently because the underlying problems (in India) are different,” he states, adding that they has already started building the needed infrastructure, recruiting a dozen AI buffs and establishing partnerships with crème de la crème educational institutions, including the IITs to give a robust push to its inspiring AI initiative.
Big data is expanding, and by next year almost a majority of businesses will be attracted towards the brighter prospect of this cutting edge technology. Even this year saw an enormous increase in volume, variety, velocity of data, which assures that the next year will witness more data, more numbers.
Data science pundits have predicted some of the leading trends that would be in the forefront in the big data revolution 2018. Come, let’s take a look:
In marketing, the analysis of data is a highly established one but the marketers nowadays have a massive amount of public and proprietary data about the preferences, usage, and behavior of a customer. The term ‘big data’ points out to this data explosion and the capability to use the data insights to make informed decisions. Understanding the potential of big data presents various technical challenges but it also needs executive talent devoted to applying the solutions of big data. Today, the marketers are widely embracing big data and are confident in their use of analytics tools and techniques. Let us learn about the ways in which Big data and analytics can improve the marketing efforts of various businesses around the around.
Previously, marketers had to frequently make guesses as to which sector of population comes under their ideal market segment but this is no longer the scenario today. The companies can exactly see who is buying and even extract more details about them with the help of big data. The other details include which buttons they generally click while on a website, which websites they visit frequently, and which social media channels they utilize.
Many retailers have introduced loyalty card systems that track the purchases of a customer, but these systems can also track which promotions and incentives are most effective in encouraging a group of customers or a single customer to make another purchase.
Because big data allows companies to optimize and monitor their marketing campaigns for performance, this implies they can allocate their budget for marketing for the highest return-on-investment (ROI).
Marketers can personalize their offers to customers in real time with the combination of big data and machine learning algorithms. Think about the Amazon’s “customers also bought” section or the recommended list of TV shows and movies from Netflix. The organizations can personalize what promotions and products a particular customer views, even down to sending personalized offers and coupons to the mobile phone of a customer when he walks into a physical location. The role of Personalized Merchandising in the ecommerce industry will continue to increase in the years to come.
Companies can conduct quantitative and qualitative market research much more inexpensively and quickly than ever before. The tools for online survey mean that customer feedback and focus groups are inexpensive and easy to implement, and data analytics make the results easier to take action.
For the past several years, sales teams, in order to rate their hottest leads, have made use of lead scoring. But, with the help of predictive analytics, a model can be generated and it can successfully predict sales and buyer behavior.
Previously, the return-on-investment for a blog post used to be highly difficult to measure. But, with the help of big data and analytics, the marketers can effortlessly analyze which pieces of content are highly effective at moving leads via a sales and marketing funnel. Even a small firm can afford to use tools for implementing content scoring which can highlight the content pieces that are highly responsible for closing sales.
Data can provide more information about your customers which includes who they are, what they want, where they are, how often they purchase on your site, and how, when they prefer to be contacted, and various other major factors. The organizations can also examine how users interact not only with their website, but also their physical store to enhance the experience of the user.
New tools for social monitoring have made it easy to gather and examine data about the competitors and their efforts regarding marketing as well. The organizations that can utilize this data will have a distinct competitive advantage.
With the help of big data, organizations can monitor their brand mentions very easily across different social channels and websites to locate unfiltered testimonials, reviews, and opinions about their company and products. The savviest can also utilize social media to offer service to the customers and create a trustworthy brand presence.
It is quite difficult to track direct ROI and impact with traditional advertising. But, big data can help organizations to make optimal marketing buys across various channels and to optimize their marketing efforts continuously through analysis, measurement, and testing.
At this point, talent and leadership are the major things that big data needs. In most of the companies, the marketing teams don’t have the right talent in place to leverage analytics and data. Apart from people who possess analytical skills to understand the capability of big data and where to use it, companies require data scientists who can extract meaningful insights from data and the technologists who can develop include new technologies. Due to this, there is a high demand for experienced analytics talent today.
In spite of all the promise, there exist certain limits to the usefulness of big data analytics in its present state. Among them, the major one is the major one is the analytics tools’ and techniques’ complex “black box” nature which makes it hard to trust and interpret the output of the approaches of big data and to assure others of the accuracy and value of the insights generated by the tools. The difficulty of gathering and understanding data also limits the capability of marketing companies to more fully leverage big data. Beyond this, the marketers are identifying many hurdles to expanding their utilization of big data tools and they include lack of sufficient technology investment, the inability of senior team members to leverage big data tools for decision-making, and the lack of credible tools for measuring effectiveness.
Cloud computing is also playing a major role in marketing with the Cloud Marketing process. Cloud Marketing is a process that outlines the efforts of a company to market their services and goods online via integrated digital experiences. Once the data analytics tools become available and accessible to even the smallest businesses, there will be a much higher impact of big data on the marketing sector as there will be much broader utilization of data analytics. This can only be a boon as organizations enhance their marketing and reach their customers in innovative and new ways.
This article was produced by Savaram Ravindra, a content contributor at Mindmajix and not by the editorial team of DexLab Analytics, a leading Hadoop training institute in Gurgaon.
Author’s Bio: Savaram Ravindra was born and raised in Hyderabad, popularly known as the ‘City of Pearls’. He is presently working at Mindmajix.com. His previous professional experience includes Programmer Analyst at Cognizant Technology Solutions. He holds a Masters degree in Nanotechnology from VIT University. He can be contacted at savaramravindra4@gmail.com. Connect with him also on LinkedIn and Twitter.
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Big data and business analytics are like two sides of the same coin. Here, though the coin represents digital transformation – but reports from consulting and services firm HCL Technologies are pointing that many companies are not being able to harness these new-age technologies to their fullest capacities resulting in a loss of digital transformation efforts.
When asked Anand Birje, the corporate vice president and head of HCL’s digital and analytics domain, he has this to say, “Over the past four or five years, enterprises were pushed hard to do anything in the field of analytics, big data and digital transformation. They were being pushed because there was this fear about what their competitors might be doing, so there was this feeling that they had to do something digital.”
Continue reading “For Long-term Digital Transformation Plan, Big Data is the Key”
According to a market research report, Global Hadoop market – industry analysis, share, size, growth, trends and forecast, which was once estimated at a value worth USD 1.5 billion in 2012, is now expected to hit $13.95 Billion mark this year, 2017 with a CAGR of 54.9%.
The advent of Hadoop platform stemmed out from the growing urge to manage problems that resulted owing to a lot of data – mostly a concoction of structured and unstructured data – that failed to fit properly in the traditional data storage and management systems, like tables. The play of analytics got intense, more complicated – both computationally and logically – hence the need for Hadoop is more than ever. This is similar to what Google was doing while it was on an endeavor to examine its user behaviors and index web pages, with a view to enhance its own performance algorithms.
Continue reading “Here’s ALL About Global Hadoop Market and Investment Report 2017”
