Category Archive: Data analyst training institute

Embedded Analytics: How it’s Revolutionizing Businesses Today?

Embedded Analytics: How it’s Revolutionizing Businesses Today?

 

Analytics is the key to modern business growth. But, developing it as a highly interactive analytical interface is challenging enough to exhaust the time and resources both. As a result, many businesses are shifting their focus to Embedded Analytics (EA) for their operations, workflows and decision-making capabilities. This new breed of analytics, known as Embedded Analytics helps businesses leverage the power of data to process them in the most useful manner.

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Write ETL Jobs to Offload the Data Warehouse Using Apache Spark

The surge of Big Data is everywhere. The evolving trends in BI have taken the world in its stride and a lot of organizations are now taking the initiative of exploring how all this fits in.

 
Write ETL Jobs to Offload the Data Warehouse Using Apache Spark
 

Leverage data ecosystem to its full potential and invest in the right technology pieces – it’s important to think ahead so as to reap maximum benefits in IT in the long-run.

 

“By 2020, information will be used to reinvent, digitalize or eliminate 80% of business processes and products from a decade earlier.” – Gartner’s prediction put it so right!

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3 Stages of a Reliable Data Science Solution to Attack Business Problems

Today, businesses are in a rat race to derive relevant intuition and make best use of their data. Several notable organizations are skimming with cutting edge data science terms and resolving intricate problems (some being more successful than others).

 

3 Stages of a Reliable Data Science Solution to Attack Business Problems

 

However, the crux lies in determining the present stage of data science your organization has embraced, followed by ascertainment of the desired level of data science.

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Quantum Internet Is Now Turning Into a Reality

Quantum Internet Is Now Turning Into a Reality
 

Scientists across the globe are looking forward towards formulating new methods to realize ‘quantum internet’, an unhackable internet, which connects particles linked together by the principle of quantum entanglement. In simple terms, quantum internet will entail multiple particles striking information at each other in the form of quantum signals – but specialists are yet to figure out what it actually does beyond that. The term ‘quantum internet’ is quite sketchy at this moment. There’s no real definition of it as of now.

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Automation Doesn’t Necessarily Make Humans Obsolete, Here’s Why

Machines are going to eat our jobs.

 

AI is handling insurance claims and basic bookkeeping, maintaining investment portfolios, doing preliminary HR tasks, and performing extensive legal research and lot more. So, do humans stand a chance against the automation apocalypse, where everything, almost everything will be controlled by robots?

 
Automation Doesn’t Necessarily Make Humans Obsolete, Here’s Why
 

What do you think? You might be worried about your future job opportunities and universal basic income, but I would ask you to draw a clearer picture about this competing theory – because, in the end, this question might not even be a plausible and completely valid question. Why, I will tell you now.

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Televisory Launches Data Analytics & Operational Benchmarking Platform

Televisory Launches Data Analytics & Operational Benchmarking Platform
 

Televisory, a start-up based out of India and Singapore, has launched its data analytics and operational benchmarking platform. The platform can measure real-time operational and financial performance of companies. While the firm has chosen to launch its platform from the US, its services are available globally.

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Google Is All Set to Wipe Off Artificial Stupidity

Well, human-AI relation needs to improve. Amazon’s Alexa personal assistant is operating in one of the world’s largest online stores and deserves accolade as it pulls out information from Wikipedia. But what if it can’t play that rad pop banger you just heard and responds saying “I’m sorry, I don’t understand the question,”!! Disappointing, right?

 

Google Is All Set to Wipe Off Artificial Stupidity

 

All revered digital helpmates including Google’s Google Assistant and Apple’s Siri are capable of producing frustrating coups that can feel like artificial stupidity. Against this, Google has decided to start a new research push to realize and improve the existing relations between humans and AI. PAIR, for People + AI Research initiative was announced this Monday, and it would be shepherded by two data viz crackerjacks, Fernanda Viégas and Martin Wattenberg.

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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.

Look for Data analyst course in Gurgaon at DexLab Analytics.

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.

Interested in a career in Data Analyst?

To learn more about Machine Learning Using Python and Spark – click here.
To learn more about Data Analyst with Advanced excel course – click here.
To learn more about Data Analyst with SAS Course – click here.
To learn more about Data Analyst with R Course – click here.
To learn more about Big Data Course – click here.

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Speaking with Tanmoy Ganguli, the expert Data Analyst Bringing Cutting Edge Technology to DexLab Analytics

Speaking with Tanmoy Ganguli, the expert Data Analyst Bringing Cutting Edge Technology to DexLab Analytics

 

DexLab Analytics is proud to announce that Tanmoy Ganguli, a proficient Data Analyst who has a long standing experience in Credit Risk Modelling, SAS and regression models is joining our Gurgaon institute as Program Director. Here are some excerpts from an interview we conducted, where he talks about the various challenges he faced in his career and the rapid development of Data Analytics.

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Skills required during Interviews for a Data Scientist @ Facebook, Intel, Ebay. Square etc.

Skills required during Interviews for a Data Scientist @ Facebook, Intel, Ebay. Square etc.
 

Basic Programming Languages: You should know a statistical programming language, like R or Python (along with Numpy and Pandas Libraries), and a database querying language like SQL

Statistics: You should be able to explain phrases like null hypothesis, P-value, maximum likelihood estimators and confidence intervals. Statistics is important to crunch data and to pick out the most important figures out of a huge dataset. This is critical in the decision-making process and to design experiments.

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