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New Intelligence is being added to Massive Storage Management System

Pioneers of High Performance Storage System (HPSS) are devising ways to streamline and rationalize data management products for its upcoming eighth generation. 25 years back, US Department of Energy research laboratories and IBM together built HPSS to support massive government science research projects. Why? The Hierarchical storage solution is undeniably a rewarding concept which uses organization policies and software automatic tricks to decide which data to save, the location where it should be saved, the best time to move it to different storage devices and when to delete it.

New Intelligence is being added to Massive Storage Management System

“How do you know what you’re archiving? We’re talking about archives now that are hundreds of petabytes to an exabyte. We think we’re going to be there in 2-3 years,” asked Todd Herr, a storage architect for supercomputing from Lawrence Livermore National Laboratory, CA.

The HPSS website catalogues 37 publicly disclosed customers, while other customers are kept discreet. At present, version 7.5.1 from last year is on the run, but version 7.5.2 might be hit, while the next year will see 7.5.3, as given in the online roadmap.

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However, version 8 is not yet available on the official roadmap, but here’s what the insiders have to say about it…

“What I think our challenge is, is to become good data curators. And I think that’s where we’re going to point the product,” Herr shared. This will turn HPSS become more capable for data mining and assign metadata to itself.

In order to do that, the first thing to be done is to reveal information in the archive about a few overarching namespace applications. Herr explained, “Right now we are working on that (referring to software made by companies such as Atempo, Robinhood, Starfish, and StrongLink). I think the next step there is scaling out metadata performance, such as database partitioning and virtualizing multiple processors when performing searches.”

Another important part of HPSS is related to the software that works with tape storage – “What we’re trying to do is enable fast access to tape. If you look across the industry spectrum, the words fast and tape generally don’t go together,” Herr intimidated. The scientists at Livermore are capable of accessing research data on tape, even that existed more than 50 years ago.

Speed-matching buffers can save the day – when placed between primary disk storage and archive tape storage, they can be used to both read and write. Some other physical improvements include faster head placements and tape motors.

“We’re going to hit a problem way faster than most sites, and certainly faster than the vendors themselves because they cannot replicate our environment in most testing,” Herr asserted.

Herr’s employer’s next supercomputer, Sierra is going to operate at up to 125 petaflops and will have a 125-petabyte file system for performing ample tests to find new ways of speeding up performance and administer advanced data storage mechanisms.

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The article has been sourced from – https://www.techrepublic.com/article/fed-and-ibm-researchers-adding-new-intelligence-to-massive-storage-management-system

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Watch Out: Top Retail Trends 2018 That Might Redefine Industry Goals

They must change – retailers finally understood this basic but true fact. For years, the retail honchos were averse to change – they preferred everything to be smooth and consistent like they were in previous years.

Watch Out: Top Retail Trends 2018 That Might Redefine Industry Goals

Now, the retail game-play is changing altogether. Today, it’s the customer who defines the entire shopping experience. No longer, storing data in traditional silos is termed as a viable option – the integration of omni-channel trade and tech-inspired merchandizing is the go-to option. Already, several well-funded retailers and global store giants are on their way to exploit the data power – they are adjusting their working mechanisms and resorting to assortment and innovations because that’s the only way to survive and sail away!

Looking ahead, here are some of the biggest retail trends to watch in 2018:

A dramatic evolution in technology

Technological transformation holds a fresh can of possibilities for retailers, but its implementation demands a lot of attention. While 2017 was reckoned to be the year of digital discovery, 2018 is going to be the year when retailers will adapt with the changing market and experience evolution in their customer’s needs. Hence, evolution will be the key to success.

Opportunities in AI are also on the rise. Chatbots, robotics and facial recognition and image recognition technologies are unleashing robust opportunities this year. Retailers are hoarding large chunks of data to curate personalized experiences for customers, and win their hearts away. More data means improved algorithm performance, and the best thing is that retailers are going on generating significant amounts of data, through both offline and online mediums. Artificial intelligence in retail can be utilized in many ways, right from improving product specifications and enhancing customer service experience.

Artificial intelligence coupled with machine learning and Internet of Things supports customer experience – there exists amazing opportunity for retailers to gain by using these new age concepts. For better data utilization, get yourself an excellent data analyst training from DexLab Analytics.

Mobile payments will usher us into a cashless economy

China has already gone cashless; thanks to AliPay and WeChat Pay. Following that, the rest of the world is looking up to the likes of Amazon Pay, Walmart Pay, Apple Pay and other types of cryptocurrencies. It’s only a matter of time before global consumers replace their plastic debit cards with more efficient and faster mobile payment options.

Work on improving offline experiences too

Not only online, but retailers should consider looking into offline experiences – how they can keep shopping as human, real and visual as possible. The mode of shopping might be transforming, but humans and their preferences are still the same. Customer experience is still important and offline experience will just focus on that.

Robotic retail is scaling up

In the E-commerce industry, the robot to human ratio is fast changing. While Walmart is testing retail robots, drone delivery is increasingly becoming popular and a viable solution. By 2020, its predicted consumer facing robots will show up in retail stores, all over.

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Improvements in technology mean a lot of retail growth. And when its technology, we can’t leave behind DATA. It’s like the new currency in the retail scenario – for a comprehensive Retail Analytics Courses, visit DexLab Analytics.

The article has been sourced from:

https://www.forbes.com/sites/pamdanziger/2017/12/27/retail-shopping-predictions-2018/#1116fcdafb33

 

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How This Bengaluru Startup Is Using AI to Detect Early Stage Breast Cancer in Women

The World Health Organization says – one out of two women diagnosed with breast cancer dies within five years in India. In the US, the fatality is less than one out of five, and in China, one out of four. Shortages of technology for early detection and radiographers coupled with the expense of regular screening, which normal people find too expensive to afford in India have led to an increasing number of breast cancer cases of late. Today, breast cancer has outstripped cervical cancer as the major cause of cancer death among women in this country.

 
How This Bengaluru Startup Is Using AI to Detect Early Stage Breast Cancer in Women
 

A Bengaluru-based tech startup and the brainchild of Geetha Manjunatha (CEO) and Nidhi Mathur (COO), NIRAMAI offers breast cancer screening solution by combining artificial intelligence, machine learning and cloud. It aims at tackling the issue of accessibility and expenses of breast cancer screening. These two dynamic women had seen cancer very closely in their family and feel an emotional connect with anyone who is diagnosed with this deadly disease. This led to the conceptualization of NIRAMAI, which means BEING WITHOUT DISEASES in Sanskrit. Also, it’s an acronym for “Non-Invasive Risk Assessment through MAchine Intelligence”.

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The Working Principle

The breast cancer screening solution by NIRAMAI is non-invasive, non-contact and non-radiation process of detecting early stage breast cancer amongst women of all ages. The deep technology that it claims to have patented is Thermalytix technology – a fusion of top-grade machine learning algorithms over thermal images.

“Thermography is well known to sense earliest signs of cancer. However, traditional manual interpretation of a thermogram has not been accurate enough to become accepted as a standard of care. Interpreting 400000 colour values in thermograms and to diagnose breast abnormality is a huge cognitive overload to a radiologist – use of machine learning enables automated analysis and helps in better interpretation of thermal images and considerably improves the overall accuracy of diagnosis”, says Geetha, one of the cofounders of NIRAMAI.

The working mechanism of screening in NIRAMAI is quite simple, and effective. The women who want to get screened need to relax for the first 10 minutes before taking up the test. Then a high resolution thermal sensor is kept at a distance of 3 feet from her to measure the temperature distribution on her chest and generate thermal images. Next, the NIRAMAI software scans these thermal images to automatically initiate a screening/diagnostic report and hands over a radiologist-certified report to the women. The test is performed in a highly intimate manner, the women undertaking the screening is neither touched nor seen by anyone.

“This is unlike mammography which is based on X-Ray and is recommended for women above 45 years only once in 2 years. It is also noncontact and doesn’t require any breast compression; hence not painful. Since the equipment is very portable, it is amenable to be used in outreach programs being a rural camp or urban corporate screening,” she shares.

Overcoming challenges

In healthcare space, analytics and AI are dubious topics. It takes a lot to coax a doctor to use an AI tool as an aid in his diagnostic procedure – countless discussions, several experimental trials and after a lot of effort, NIRAMAI could finally step into and create a niche of their own.

Another challenge was to have an edge over their competitors, who once knew that they are out with a revolutionizing technology, would like to sell everything to copy that. For that, they have armed themselves with 10 patents in this area, which is somewhat protecting them from other players.

Since breast cancer is a big health issue in India, the NIRAMAI team feels that it is extremely important for women to go for regular screening. It is safe and in most cases, early detection helps keep cancer at bay.

The power of analytics is huge. Arm yourself with a powerful data analyst certification Delhi NCR. It will help you go a long way!

Some parts in this blog have been sourced from:

https://analyticsindiamag.com/this-women-led-startup-is-using-ai-thermal-imaging-to-detect-breast-cancer

https://www.techinasia.com/startup-patented-ai-tech-breast-cancer-screening

 

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Data Analytics: The Key to Track and Curb Leakages in GST

Though our country may have got a One Nation, One Tax Policy, in the face of GST, its revenue collection figures are not so encouraging. In the beginning, GST revenue collection for the first three months went over 90000 crore, but the figures started dropping from October to 83346. And in November, it further slipped to 80808 crore. Since then, the figures mostly lingered around 86000 in the recent months.

 
Data Analytics: The Key to Track and Curb Leakages in GST
 

The Union Ministry of Finance had to figure out the reason of this discrepancy, the reason behind such huge revenue leakage in GST collection before it’s too late, and for that data analytics came to the rescue. After carrying out a thorough analysis, on its 26th meeting on Saturday, GST Council discovered several major data gaps between the self-declared liability in FORM GSTR-1 and FORM GSTR-3B.

 

Highlighting the outcome of basic data analysis, the GST Council stated that the GST Network (GSTN) and the Central Board of Excise and Customs have found some inconsistency between the amount of Integrated GST (IGST) and Compensation cess paid by importers at customs ports and input tax credit of the same claimed in GSTR-3B.

 

 

“Data analytics and better administration controls can help solve GST collection challenges” – said Pratik Jain, a national leader and partner, Indirect Tax at PricewaterhouseCoopers (PwC).

 

He added, “Government has a lot of data now. They can use the data analytics to find out what the problem areas are, and then try and resolve that.” He also said that to stop the leakage, the government need to be a lot more vigilant and practice better controls over the administration.

 

Moreover, of late a parliamentary committee has found that the monthly collection from GST is not up to the mark due to constant revisions of the rates, which has undoubtedly affected the stability of the tax structure and had led to an adverse impact for trade and business verticals.  

 

 

“The Committee is constrained to observe the not-so-encouraging monthly revenue collections from GST, which still have not stabilised with frequent changes in rates and issue of notifications every now and then. Further, the Committee is surprised to learn that no GST revenue targets have been fixed by the government,” said M Veerappa Moily, the head of Standing Committee on Finance and a veteran Congress leader in a recent report presented in the Parliament.

 

The original article appeared inanalyticsindiamag.com/government-using-data-analytics-to-track-leakages-in-gst/

To experience the full power of data analytics and the potentials it withholds, find a good data analyst training institute in Delhi NCR. A reliable data analytics training institute like DexLab Analytics can help you unearth the true potentials of a fascinating field of science – go get details now.

 

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The role of Big Data Analytics in the World of Media and Entertainment

The role of Big Data Analytics in the World of Media and Entertainment

A reverberating revolution is on the go in the media industry. Reason: thorough digitization and data-driven marketing.

A seamless amalgamation between digital and analytical solutions is transforming versatile media platforms across the globe. Not only does it help in curating more personalized content for its niche audiences, but also bolsters newer capabilities, such as master data management for digital assets and improved customer engagement programs.

Is Big Data Big Enough?

Facebook gathers and processes more than 500 TB of data every day.

Google processes 3.5 billion requests every day.

Amazon records 152 million customer purchase data every day.

With the rise of digitization, media and entertainment companies are leveraging big data technology like no other for better customer engagement.

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Here are a few examples showing how media companies are using the power of big data:

In predicting audience preference

Large chunks of data helps in predicting and understanding the demand of audiences – right from the genre of shows and music they like to content selection for a given age group or for different channels.

Better acquisition and retention

Any day, big data help to fathom the reasons why consumers subscribe or unsubscribe a particular channel. It aids companies in developing robust promotional and product strategies to attract and retain more loyal user base. Social media data also lend a helping hand to enhance consumer interest.

Content revenue generation and new product development

With the power of accurate and productive data, media houses incentivize consumer behavior and while doing so, they understand the true market value of the content generated.

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How Media Uses Data Anaytics?

Netflix

Netflix assimilates large chunks of viewership data, with which it performs an in-depth analysis of viewer’s behavior for millions of viewings of shows. The analysts conduct thorough research on the attributes and qualities of data about consumers to know which show is the most popular. This analysis also helps them know how long viewers are watching a program or season or any individual show. Hence, in this way it outbids its competitors and owns rights to showcase blockbuster hits.

Bollywood

Talking about our very own Bollywood, SRK’s Chennai Express used big data and analytics to boost social media presence and digital marketing endeavors. And, no wonder, it smashed the box office records of 2013. It became such a raging success that the IT services company Persistent Systems released a statement saying, “Chennai Express related tweets generated over 1 billion cumulative impressions and the total number of tweets across all hashtags was over 750 thousand over the 90-day campaign period.”

This is a single instance. Many other bigwig producers have time and again collaborated with cutting edge big data analytics firms to better understand consumer trends and drive customer engagement.

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Conclusion

Big Data is a surefire boon for media and entertainment houses; it helps companies to solve crucial questions about consumers, things they like, content they feed in, and shows they treasure. Moreover, it aids in tracking clicks, shares and views across multiple devices and media platforms.

To lead the change, join DexLab Analytics. Their Data analyst course in Delhi NCR is surely worth taking up to fulfill all your divine career aspirations. Check out business analytics course itinerary now.

 

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3 Ways to Increase ROI with Data Science

3 Ways to Increase ROI with Data Science

In 2018, companies have decided to invest $3.7 trillion on machine learning and digital transformation so as to embrace a promising return on that sizeable investment for professionals involved in managerial roles. Nevertheless, 31% of the companies using the potent tools of machine learning and data science are not yet tracking their ROI or are in no mood to do so in the near future.

But to be on the side, ROI is very crucial for any business success – if you fail to see the ROI you expect from data science implementation, look into bigger and complex processes at work – and adjust likewise.

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Take cues from these 3 ways, explained below:

Implementing data science strategy into C-Suite

According to Gartner, by next year 90% of big companies would hire a Chief Data Officer, a promising role that was almost nonexistent a few years ago. Of late, the term C-Suite is gaining a lot of importance – but what does it mean? C-Suite basically gets its name from a series of titles of top level executives who job profile name starts with the letter C, like Chief Executive Officer, Chief Financial Officer, Chief Operating Officer and Chief Information Officer. The recent addition of CDO to the C-Suite has been channelized to develop a holistic strategy towards managing data and unveil new trends and opportunities that the company has been attempted to tab for years.

The core responsibility of a CDO is to address a proper data management strategy and then decode it into simple, implementable steps for business operations. Its prime time to integrate data science into bigger processes of business, and soon company heads are realizing this fact and working towards it.

Your time and resources are valuable, don’t waste them

Before formulating any strategy, CDOs need to ensure the pool of professionals working with data have proper access to the desired data tools and support or not. One common problem that persists is that the data science work that takes place within an organization is done on silo, and therefore remains lost or underutilized. This needs to be worked out.

Also, besides giving special attention on transparency, data science software platforms are working towards standardizing data scientists’ efforts by limiting their resources for a given project, thereby ensuing cost savings. In this era of digitization, once you start managing your data science teams efficiently, half the battle is won then and there.

Stay committed to success

Implementing a sophisticated data science model into production process can be a challenging, lengthy and expensive process. Any kind of big, complicated project will take years to get completed but once they do, you expect to see the ROI you desire from data science but the journey might not be all doodle. It will have its own ups and downs, but if you stay committed and deploy the right tools of technology, better outcome is meant to happen.

In a nutshell, boosting of ROI is crucial for business success but the best way to trigger it would be by getting a bird’s eye view of your data science strategy, which will help in predicting success accurately and thus help taking ROI-supported decisions.

If you are looking for a good data analyst training institute in Delhi NCR, end your search with DexLab Analytics. Their data analyst certification is student-friendly and right on the point.

 

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How Can You Improve Your Business Figures with Data Lakes

Today, data lakes are springing up here and there. And with that, the composition structure of data lakes is changing. As more and more data are moving towards cloud, data lakes are shifting focus towards cutting edge sources, like NoSQL, while cloud data warehouses are emerging across hybrid deployments.

How Can You Improve Your Business Figures with Data Lakes

A humongous amount of data is being churned out on digital platform each day. IBM says as much as 2.5 quintillion bytes of data is created on a daily basis. Now, this ever-expanding amount of data needs for proper storage system – for that, data lakes have been constructed to hold data in its raw form. In these vast storehouses, data remain mostly in their unstructured state, which is pulled out by data scientists to remodel and transform them into versatile data sets for future use.

Continue reading “How Can You Improve Your Business Figures with Data Lakes”

Internet of Things: It’s Much More Than What It Appears to Be

Internet of Things: It’s Much More Than What It Appears to Be

What’s all the hype about “the next big thing”? Have you got it yet? Nope? It’s not owing to a lack of imagination, but an observation.

Currently, the Internet of Things is the big buzz. It’s all about enhancing machine-to-machine communication – being structured on cloud computing and systems of data-gathering sensors, the connection is entirely virtual, mobile and instantaneous.

Big Data And The Internet Of Things – @Dexlabanalytics.

What is IoT?

In simple terms, the concept of IoT stresses on connecting any device with the Internet – including cellphones, headphones, washing machines, lamps, coffee makers, wearable devices and almost anything that comes in your mind. The IoT is a colossal network of connected Things (inclusive of people) – the famous analyst firm Gartner says by 2020 there will be more than 26 billion connected devices in this world.

Explaining the Everlasting Bond between Data and Risk Analytics – @Dexlabanalytics.

What makes it so popular?

As we now know, IoT is a network of things and people, where communication takes place through numerous wireless and wired technologies and it comes with a wide set of advantages. Following are some of the advantages of this new breed of technology:

A better, less-complicated life

Imagine a life, where what you seek will be delivered to you right away, before you even ask for it. It may appear to you that you are dropped right into a scene from your favorite sci-fi movie or novel – the moment your morning alarm starts ringing, your bathtub automatically starts getting filled with hot water; when you leave your home, the lights get turned off automatically and doors lock itself on its own; your car takes you to the office through the less-congested roadway and when you return home, your home lights automatically start to switch on and lastly your air conditioner adjusts the temperature of your room once you are ready to hit the bed. Proper use of IoT makes your life easier and effortlessly simple.

Is Change the Only Constant: How Analytics has Changed, while Staying the Same Over the Last Decade – @Dexlabanalytics.

Less accident, better safety

How would it be if for an example you get a heart attack while driving back home and your smartwatch detects it and deploys autopilot mode in your car so that it straightaway takes you directly to the nearest hospital? On the way, your cellphone can dial up the hospital staffs and inform them about the current condition of the patient to help you get the best treatment possible.

Harnessing the power of data

Utilizing the power of data is awesome. Harnessing data to simplify things is the next best thing in today’s world. Living a life straight out of sci-fi movies is awesome, but practically, there’s still some time left for IoT to become a hardcore reality. Once IoT makes its way into our lives, a set of smart devices powered by sensors will take charge and make almost everything possible – whether it’s switching on the AC automatically when a person enters the room or driving a car to a destination without any driver.

IoT helps in taking better decisions in the best interest for businesses

Beyond making your lives easier, IoT possesses a bunch of capabilities – it’s a robust technology that collects the most valuable resource, i.e. data. Data helps businesses take better, well-informed decisions. 

Of all the recent technological developments, Internet of Things is considered to be one of the biggest trends to watch out for. In the next 5 years, it’s going to change lives forever!

To know more about the Internet of Things and more such digital trends, why don’t you settle for a good business analytics course in Delhi! DexLab Analytics is a premier Data Science training institute Gurgaon that offers hands-on experience to students alike.

 

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6 FAQs to Get Acquainted With the Fundamentals of Big Data

6-FAQs-to-Get-Acquainted-With-the-Fundamentals-of-Big-Data

By mobilizing the volume and wealth of information in an organization, Big Data leads to improved customer perceptiveness, competitive advantage and operational efficiency. In the current data-centric era, big data is the buzzword. Nevertheless, how many of you actually know what it entails?

In this blog, we have compiled few FAQs, which will instantly shed some light about the basics of Big Data and its implementation.

Also read: Tigers will be safe in the hands of Big Data Analytics

What is Big Data?

Substantially complex, big data involve hundreds and thousands of terabytes or exabytes of data (starts with 1 and has 18 zeros after it, or 1 million terabytes) per single data set. If explained in simple words, big data is a collection of data sets, which comes from a variety of sources, like customer data, Internet of Things and social media. If compiled and analyzed in the right manner, it helps in understanding the nature of the lifestyle and purchasing habits of people and customers better.

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To be called Big Data, how much data is needed?

The answer to this question is a bit challenging. Depending on the infrastructure of the market, the threshold limit of big data is determined. In most of the cases, the lower boundary of big data is limited to 1 to 3 terabytes.

However, using big data technologies for small databases can prove to be effective. Netezza brings about 200 built-in computer programs, like Python and Revolution R, which gained immense appreciation for being applicable to small databases.

Also read: Why Getting a Big Data Certification Will Benefit Your Small Business

Is there any use of intuition in the current epoch of big data? Have machines completely superseded the human mind?

Intuition is consequential, as ever. Staring at the humongous amount of data compels us to start from somewhere. As there is so much data, intuition is important, like never before. If you ask me, big data hasn’t yet replaced intuition, in fact the latter somehow complements the former. Both of them share a continuum relationship, instead of binary.

What are the main sources of big data?

Transactional data, social data and machine data- are the chief sources of big data. Top-notch retailers like Amazon and Dominos boasting of more 1 million customer transactions per day results in to the generation of petabytes of transactional big data. Social media data comprise of 230 million tweets on Twitter per day, more than 60 hours of video uploaded every minute on YouTube and 2.7 billion Likes and Comments on Facebook appearing every day. Lastly, machine data can be boiled down to various modes, including the information generated by industrial equipment, web logs tracking behavioural data and real-time data emanating from sensors.

Also read: Big Data is the New Obsession of Small Business Owners

Is data visualization gaining popularity?

Adopt interactive data visualization tools and take your business to new heights. These tools are rewarding, say thanks to Big Data! Big conglomerates, like Google, Netflix, Amazon, Apple, Facebook and Twitter embraced the tools to visualize data. And this goes beyond the basic usage of graphs, excel charts and pivot tables.

Is big data going to last?

Well, yes, very much so. Big Data is leading the future and is going to stay HERE AND NOW. It is right on its way to fundamentally transform the ways in which companies function and regard their competitors, customers and overall business.

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