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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 to Develop a Data-Driven Culture among the Employees and Organization?

Data creation and consumption is exploding. So is the challenge of analyzing data and transforming it into actionable insights.

How to Develop a Data-Driven Culture among the Employees and Organization?

The expert consultants at IBM say – 90% of the data in the world has been created in the last couple of years at a rate of 2.5 quintillion bytes per day. Just imagine, when such gold mines of information go unused, what toll does it take on companies who harbors them? The loss is insurmountable, isn’t it? 

But the question that makes us brood is how do companies empower employees to use such vast pools of data to reveal hidden business insights?

To keep pace with an accelerating growth of data generation and robust competitive landscape, new age companies need to shift their focus to sound Business Intelligence solutions that helps in collecting and analyzing data to determine patterns and alert users, in case of anomalies in the nature of business. And the good news is that they are doing so.

Once companies start off with data handling and data mining, the issue of utilization needs to be addressed next – the trickiest problem with data utilization is the insights that take place within the departments –while creating data silos. Siloed data results in creating a lot of issues, but the larger one is that it creates only a partial view of whatever is happening within an organization and a bigger picture is not available.

As a result, a data-driven culture is to be adapted – but how?

 

Let’s Take Your Data Dreams to the Next Level

Right from the top-level

The true DNA of any organization lies within its top-level management team, including the founders and managing directors – and that’s where the foundation stone of data-driven culture should be implanted. Implementing something new and offbeat is intimidating, but when the company leaders promote it, the idea gains familiarity and merges with other data-driven decisions.

Empowerment

Employees need to feel empowered – then only they can independently mine data and share crucial findings with colleagues and seniors without asking for help from the IT guys. A common misconception that exists around is that data analytics is a cumbersome task which requires heavy involvement from IT- but in reality, things are changing – BI tools are being revamped to make users more independent and self-sufficient to take better business decisions.

Time and again, it’s important for the executive management to show some token of appreciation to employees for their hard work. It is in these subtle ways the data-driven culture gets promoted across company walls.

 

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Sharing is caring

Now, the data siloes come into the picture. Once employees are comfortable with using data and bearing the fruits of success – insights need to be shared across the business fronts to draw a much larger picture.  Not only it promotes cross-team and departmental collaboration, but also brings in newer data into the limelight that wouldn’t have been possible before. Hence, sharing of insights is crucial for business success.

From the above discussion it is clear, insights gained from data is extensively beneficial for business, as they offer new answers for innovation and development. However, achieving data nirvana is no mean feat – the steps highlighted above should be followed, and then only the companies would be able to achieve their desired goal, i.e. a seamless data-driven culture.

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Sources: http://dataconomy.com/2017/05/data-nirvana-develop-data-driven-culture

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.

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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/

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Big Data, Hadoop and Cloud: The Looming Challenges and How to Peg Them?

Big Data, Hadoop and Cloud: The Looming Challenges and How to Peg Them?

Data is regarded as the “new oil” in the industry – though you can’t fill your car’s gas tank with binary digits, but yes, you can definitely think of driving an autonomous car with data. Self-driven cars are a reality now!

About 10 years ago, with the advent of big data hype, organizations, big and small joined the bandwagon involving data so as not to miss out the ‘next big thing’. The whole thing started with the ‘data land grab’ phase. Next came the delineation phase, in which industry started chalking out clearly big data boundaries and where it has to be applied. After this, we have moved into an efficiency phase – whereby we extract the maximum out of data by merging right expertise with the right technology.

Notwithstanding all the exciting stuffs surrounding big data, many challenges have even come out during the delineation phase and they still continue to cripple company functioning. So, here we will talk about the challenges faced and ways to tackle them…

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Big Data Challenges

Now, it’s the time for humongous volumes of unstructured data – companies have as a result shifted their focus from traditional big data storage solutions to more agile, cost-efficient open source strategies like Spark and Hadoop. Navigating through a turbulent sea of big data tools is another daunting task in itself, so here we will address the issue of Hadoop challenges only.

Though Hadoop has solved a multitude of data problems, yet its implementation and management is a difficult task, and ends up causing more problems than doing good. Also, scaling Hadoop on premise is a taxing procedure, involving a lot more investment in physical infrastructure – for this, many companies are turning towards cloud-based Hadoop solutions because they are agile and less complicated to use.

Cloud Migration Challenges

Cloud-based solutions help companies maneuver in a more agile manner, while enhancing their data needs. This acts as a robust solution to the issue of adding more on-prem infrastructure over time, but as it’s said, there’s no gain without pain – migrating data analytics to a purely cloud infrastructure has its own cons.

The biggest challenges associated with cloud network are related to reliability, performance, scalability and accessibility of data. Data security also remains a matter of concern – a handful number of recent high-profile data breaches have made us vulnerable, while showing on our face how less protected we are in the digital world.

How To Tackle the Emerging Challenges?

Think beyond today! Companies need to make their headstrong big data solutions future proofed, because no one likes to do the same thing again and again in a time span of two-three years. If you are incorporating steady solutions today, make sure they stay in practice for the coming 5-10 years or so.

As we have mentioned earlier, Hadoop implementation and management is not as easy as it sounds, and gaining access to a deft pool of experts who understands the intricacies of Hadoop has become the need of the hour. This means, make sure you choose the right internal talent pool and work with uber talented experts.

Now, when it comes to ensuring data security over cloud infrastructure, make sure you think beyond the perimeter security, focus on identifying sensitive data, both structured and unstructured and then secure it in a Hadoop lake just the way it’s ingested. This will help you closely monitor cloud data sources and check violations right from the start.

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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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Why Your Business Needs a Chief Productivity Officer: 5 Reasons Explained

For smooth use of technology, businesses look forward to CIOs. But that’s so passé now. This position is now losing its relevance more and more, as other notable features like migration of business applications and storage on the cloud are enhancing their capabilities.

 
Why Your Business Needs a Chief Productivity Officer: 5 Reasons Explained
 

As such, a new business position: Chief Productivity Officer (CPO) is sprouting out – this job profile dictates all the services, while ensuring your organization meets every goal.

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How Data Scientists are Merging Professional and Personal Resolutions for a Career Boost in 2018

The beginning of a year comes with a wide stream of promises! Some decide to work on their physique, while others look forward to visit a new country, but budding data scientists are found thinking of something else.

How Data Scientists are Merging Professional and Personal Resolutions for a Career Boost in 2018

Here goes a chart down of what goes on in a mind of a data scientist, who could stare for hours at the computer screen pondering which code or query to run…

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How Careers in Tech is Getting Influenced Due to CryptoCurrency Revolution

Cryptocurrency is the new in-thing that is creating a lot of buzz in the tech world. And though your friends and family might be hearing all good things about Bitcoin, you will be surprised to know – it’s creating job. Yes, you heard it right – cryptocurrency is exploding the job market. From startups to blue chip companies, everyone is talking about the perks of blockchain and what it potentials it holds for future.

 
How Careers in Tech is Getting Influenced Due to CryptoCurrency Revolution

Job trends to follow

Going by the reports uploaded by job search site Indeed, job postings for bitcoin, blockchain and cryptocurrency have increased by more than 620% since November 2015. In fact, the search ratios for such jobs have also increased by 1065%, suggesting supply is expanding along with demand.

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