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How India is driving towards Data Governance

Data is power – it’s the quintessential key to proper planning, governance, policy decisions and empowering communities. In the recent times, technological expansion is found to be contributing immensely towards ensuring a sustainable future and building promising IT base. Robust developments in IT related services have resulted into key breakthroughs, including Big Data, which as a result have triggered smooth data governance.

How India is driving towards Data Governance

According to a NASSCOM report, India’s analytics market is expected to grow from $1 billion to $2.3 billion in the year 2017-18. However, the fuller benefits of data analytics are yet to be channelized by the public sector.

In a varied country like India, data collection is a lengthy procedure. At present, information is being collected by various government departments straight from Panchayat levels to state levels. Though, most of the data remains trapped within department walls, it is largely used to pan out performance reports. Also, certain issues in timely collection of data pops up, while sometimes the quality of data collected becomes questionable, hence delaying the entire analysis.

 

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Quality data plays an integral role, if analyzed properly at the proper time. They can be crucial for decision-making, delivery of services and important policy revisions. As a matter of fact, last year, Comptroller and Auditor General (CAG) initiated Centre for Data Management and Analytics (CDMA) to combine and incorporate relevant data for the purpose of auditing. The main purpose here is to exploit the data available in government archives to build a more formidable and powerful Indian audit and accounts department.

Indian government is taking several steps to utilize the power of data – Digital India and Smart Cities initiatives aim to employ data for designing, planning, managing, implementing and governing programs for a better, digital India. Many experts are of the opinion that government reforms would best work if they are properly synchronized with data to determine the impact of services, take better decisions, boost monitoring programmes and improve system performances.

Open Data Policy is the need of the hour. Our government is working towards it, under the jurisdiction of the Department of Information and Technology (DIT) to boost the perks of sharing information across departments and ministries. Harnessing data eases out the load amongst the team members, while ensuring better accountability.

Tech startups and companies that probe into data and looks for solutions in data hoarding and analytics to collect and manage complicated data streams need to be supported. The government along with local players should encourage citizens to help them in collecting adequate information that could help them in long-run. India is walking towards a rapid economic development phase, where commitment towards information technology, data governance and open-source data is of prime importance. For the overall economy, bulk investments in capacity building, technology implementation and data-facilitating structures should be considered and implementable to bring plans and participation into place to hit off a better tech-inspired reality.

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The original article appeared on – https://economictimes.indiatimes.com/small-biz/security-tech/technology/indias-investment-in-big-data-will-ensure-governance/articleshow/57960046.cms

 

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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.

Accelerate your career with business analyst training Delhi NCR. DexLab Analytics offers 360-degree Data Science Online training in Delhi – interested candidates please visit the website.

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.

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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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.

Continue reading “Why Your Business Needs a Chief Productivity Officer: 5 Reasons Explained”

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.

Continue reading “How Careers in Tech is Getting Influenced Due to CryptoCurrency Revolution”

Data Science: Is It the Right Answer?

‘Big Data’, and then there is ‘Data Science’. These terms are found everywhere, but there is a constant issue lingering with their effectiveness. How effective is data science? Is Big Data an overhyped concept stealing the thunder?

Summing this up, Tim Harford stated in a leading financial magazine –“Big Data has arrived, but big insights have not.” Well, to be precise, Data Science nor Big Data are to be blamed for this, whereas the truth is there exists a lot of data around, but in different places. The aggregation of data is difficult and time-consuming.

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Statistically, Data science may be the next-big-thing, but it is yet to become mainstream. Though prognosticators predict 50% of organizations are going to use Data Science in 2017, more practical visionaries put the numbers closer to 15%. Big Data is hard, but it is Data Science that is even harder. Gartner reports, “Only 15% organizations are able to channelize Data Science to production.” – The reason being the gap existing between Data Science expectations and reality.

Big Data is relied upon so extensively that companies have started to expect more than it can actually deliver. Additionally, analytics-generated insights are easier to be replicated – of late, we studied a financial services company where we found a model based on Big Data technology only to learn later that the developers had already developed similar models for several other banks. It means, duplication is to be expected largely.

However, Big Data is the key to Data Science success. For years, the market remained exhilarated about Big Data. Yet, years after big data infused into Hadoop, Spark, etc., Data Science is nowhere near a 50% adoption rate. To get the best out of this revered technology, organizations need vast pools of data and not the latest algorithms. But the biggest reason for Big Data failure is that most of the companies cannot muster in the information they have, properly. They don’t know how to manage it, evaluate it in the exact ways that amplify their understanding, and bring in changes according to newer insights developed. Companies never automatically develop these competencies; they first need to know how to use the data in the correct manner in their mainframe systems, much the way he statisticians’ master arithmetic before they start on with algebra. So, unless and until a company learns to derive out the best from its data and analysis, Data Science has no role to play.

Even if companies manage to get past the above mentioned hurdles, they fail miserably in finding skillful data scientists, who are the right guys for the job in question. Veritable data scientists are rare to find these days. Several universities are found offering Data Science programs for the learners, but instead of focusing on the theoretical approach, Data Science is a more practical discipline. Classroom training is not what you should be looking for. Seek for a premier Data analyst training institute and grab the fundamentals of Data Science. DexLab Analytics is here with its amazing analyst courses in Delhi. Get enrolled today to outshine your peers and leave an imprint in the bigger Big Data community for long.

 

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More Than Fifty Percent Companies Lack Required Tools and Investment for Efficient Business Analytics

More Than Fifty Percent Companies Lack Required Tools and Investment for Efficient Business Analytics

Fifty-nine percent of the companies around the world are not using Predictive Models or Advanced Analytics – says Forbes Insights/Dun & Bradstreet Study.

A recent study by Forbes Insights and Dun & Bradstreet, “Analytics Accelerates Into the Mainstream: 2017 Enterprise Analytics Study,” elucidates the ever-increasing indispensable role that analytics play in today’s business world, all the way from devising strategies to operations. The gloomy Forbes study highlights the crucial need for immediate investment, implementation and prioritization of analytics within companies.

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The survey was carried on more than 300 senior executives in Britain, Ireland and North America and the report illuminates that the leading corporate giants need to invest more on the people, the processes they use and technologies that authorize decision support and decision automation.

Bruce Rogers, chief insights officer at Forbes Media was found quoting, “This study underlines the need for continued focus and investment,” he further added, “Without sophisticated analysis of quality data, companies risk falling behind.”

“All analytics are not created equal,” said Nipa Basu, chief analytics officer, Dun & Bradstreet.  She explained, “This report shows a critical opportunity for companies to both create a solid foundation of comprehensive business data – master data – and to utilize the right kind of advanced analytics. Those that haven’t yet begun to prioritize implementation of advanced analytics within their organizations will be playing catch-up for a long while, and may never fully recover.”

 

Key findings revealed:

Need for tools and best practices

Though data usage and consumption growth brags about success, little sophistication is observed in how data are analysed. Only 23% of the surveyed candidates are found to be using spreadsheets for all sorts of data work, while another 17% uses dashboards that are a little more efficient than spreadsheets.

The survey says mere 41% rely on predictive models and/or advanced analytical and forecasting techniques, and 19% of the respondents implement no analytical tools that are more complicated than fundamental data models and regressions.

Skill deficiency stalling analytics success

Twenty seven percent of respondents diagnosed with skill gaps as a major blocker between current data and analytics efforts. Fifty two percent were found to be working with third-party data vendors to tackle such lacks of skills. Moreover, 55% of the surveyed contestants said that third-party analytics partners performs better than those who works in-house, exhibiting both a shortage of analytics capabilities among in-house analysts and a dearth in skilled workers.

Investment crunch

Survey respondents ticked lack of investment and problems with technology as the top hindrances to fulfilling their data strategy goals. Despite the increasing use of data, investment in deft personnel and technology is lagging behind.

CFO’s introspect into data for careful insights

According to the survey, 63% of those who are in the financial domains shared they are using data and analytics to discover opportunities to fund business growth. Further, 60% of the survey respondents revealed they rely on data to boost long-term strategic planning.

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