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Microsoft Excel is Revamping Itself and We Can’t be Happier

Good News: Your favorite Microsoft Excel is about to get a lot smarter, and tech-savvy.

 
Microsoft Excel is Revamping Itself and We Can’t be Happier
 

How? Thanks to machine learning and improved connection with the outside world.

 

Recently, Microsoft’s general manager for Office, Jared Spataro and company’s director of Office 365 ecosystem marketing, Rob Howard talked about how Excel is soon going to understand more about the inputs given and drag out additional information from the internet, as and when deemed necessary.

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Cyber Value-at-Risk Model: Quantifying the Value-at-Risk

Cyber Value-at-Risk Model: Quantifying the Value-at-Risk

Cybersecurity attacks are the new potent threat to businesses. Diligent professionals and big mouth board members have started reviewing their company’s cybersecurity frameworks, while establishing better security controls and discerning deeper insights about the business impact of cybersecurity attacks: what kind of risks are they exposed to? Are they expending too much and need to curtail down? What amount of risk can be reduced using the proposed info security budget? Cyber-insurance, will it fetch better results?

What objectives to secure with Cyber value-at-risk models?

This is the epic question that has triggered the development of Value-at-risk models, especially in the domain of information security. Also known as Cyber VaR, these models are a game-changer. They offer a sound base for quantification of information risk coupled with infusing discipline into the whole process.

Market Risk Analytics: What It is All About – @Dexlabanalytics.

The objective of VaR is:

  • To help risk professionals formulate the notion of cyber risk in plain financial language without using any technical jargons.
  • To enable business professionals achieve a standard balance between safeguarding an organization and running the business by making cost-effective decisions.

Enterprises powered by VaR models for cybersecurity make complicated decision-making as easy as pie. They trigger risk-related discussions, where risks become more consistent, and business-goal driven.

A New Course Alert! DexLab Analytics Launches Market Risk Analytics and Modelling – @Dexlabanalytics.

What exactly is cyber VaR?

In the world of finance, value-at-risk modeling is the statistical methodology to appraise the level of financial risk that a firm is exposed to over a specific period of time.

The VaR is ascertained using these three variables:

  • The amount of conjectured loss
  • The probability of that amount of loss
  • The time frame

Probabilities are effective to evaluate likely losses from the cyber attacks during a specific time period. Top notch global organizations, like World Economic Forum and several regulatory bodies, like The Open Group are revolutionizing the concept of cyber VaR models.

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What is its benefit?

VaR was initially developed in 1990’s to boost the investment banking sector, wherein managers were to identify the risks that popped up daily in multiple market reports. From the name itself, you can understand, it is more likely a measurement tool to analyze the financial impact of risky events within a particular time frame.

The most beneficial effect of VaR is that it not only quantifies risk but also pens it down in economic terms that are easily understood by all. It also assists in mitigating long-term challenges by aggregating cyberrisk with various other operational risks within an enterprise risk management system.

Here’s All You Need to Know about DexLab Analytics’ Market Risk Modelling Live Demo Session – @Dexlabanalytics.

How to determine the value of cyber VaR?

 CISOs, Chief information security officers decipher what exactly VaR offers in terms of cyberrisk management. This hi-tech concept is too good to help with crucial decision-making, like addressing cyberrisk appetite and defining the optimal allocation of cyber risk management resources.

Market risk analytics is a new concept in the make. Many organizations have realized its crucial importance, while many are yet to decipher. For the best enterprise risk management certification, drop by DexLab Analytics. They are a leading economic capital model training institute offering state-of-the-art courses to the candidates.

 

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Discover the Best Industries to Have a Career in Data Science

Discover-the-Best-Industries-to-Have-a-Career-in-Data-Science

Data fires up everything, nowadays. And data science is gaining exceptional traction in the job world, as data analytics, machine learning, big data, and data mining are fetching relevance in the mainstream tech world. By 2025, it is being expected that data science industry will reach $16 billion in value – this is why landing a job in data science domain is the next big thing!

The skills you will imbibe as a data scientist would be incredible, powerful and extremely valuable. You can easily a bag a dream job in corporate moguls, like Coca-Cola, Uber, Ford Motors and IBM, as well as play a significant role in any pro-social or philanthropic endeavors to make this world a better place to live in.

Check out these extremely interesting fields you could start your career in data science:

Biotechnology

No wonder, science and medicine are intricately related to each other. As the technology pushes boundaries, more and more companies are recommitting themselves towards a better public health by nabbing biotechnology. Being a data scientist, you would help in unraveling newer ways of studying large amounts of data – including machine learning, semantic and interactive technologies. Eventually, they would influence treatments, drugs-usage, testing procedures and much more.

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Energy

Power industry functions on data – and tons of it. Whether it’s about extracting mineral wealth from the earth’s crust or transporting crude oil or planning better storage facilities, the demand for data scientists is on the rise. Just as expanding oil fields ask for humongous amounts of data study, installing and refining cleaner energy production facilities relies on data about the natural environment and ways of modern construction. Data scientists are often given a ring to enhance safety standards and help companies recommit themselves towards better safety and environmental regulations.

Transportation

Recently, transportation is undergoing a robust change. For example, Tesla paved a new road of development and turned countless heads by unveiling a long-haul truck that could drive on its own. Though it’s not the first time, they are prone to lead the change.

Beyond self-driving vehicle technology, the transportation industry is looking for more efficient ways to preserve and transport energy. These advancements in technology works wonders when combined with better battery technology development – in simple terms, every individual field in transportation industry is believed to benefit from a motley team of data scientists.

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Telecommunications

The internet is not only about tubes, but all about data. The future of the internet is here, with ever-increasing networks of satellites and user devices establishing communication through blockchain. Though they are yet to be used on large-scale, they have started making news. In situations like this, it would be difficult not to highlight the importance of data science and data architecture as they are becoming major influencers in the internet world. Whenever there is a dire need to make the public aware of a new product, we rely on user data – hence the role of data scientists is the key to a better future.

Today, data science is an interesting field to explore, and it is going to play an integral role as the stride in technology and globalization keeps expanding its base. If you have a keen eye for numbers, charts, patterns and analytics, this niche is perfectly suitable for you.

DexLab Analytics is a prime Data Science training institute Delhi that excels in offering advanced business analyst training courses in Gurgaon. Visit our official site for more information and make a mark in data analytics!

 

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Time to Change the Game of Online Lending With AI and Big Data

Time to Change the Game of Online Lending With AI and Big Data

As digitization grows in size and width, more and more companies are seeking ways to modify their digital lending services. It would be effective as well as profitable for both borrowers and lenders. And as a topping on the cake, companies resort to Artificial Intelligence and Big Data as they believe they are the future powerhouse of loans.

Originally banks being the lenders make the lending decision based on a loan applicant’s credit score – which is a 3-digit number collected from renowned credit bureaus, like Equifax and Experian. Credit scores are obtained from large piles of data, such as credit history length, payment history and credit line amounts, and are used to decide whether the applicants would be able to repay their debts. They are also good to determine the interest rate of loans.

online-lending

Low credit score is an indication that you are a risky borrower, which may end up in rejection of your loan application or else you have to pay excessively higher interest rate.

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Artificial Intelligence: What the Future Holds for India, Next to US – @Dexlabanalytics.

However, according to digital lending platforms, this kind of information isn’t enough – they fail to draw the actual picture of the loan applicant’s credit worthiness. Rather, it is advisable to include hundred other data points in the scrutiny process, and they don’t have to be based on financial interactions alone. Include educational certifications, employment documents, and even you can take help from minor information, like your nap time, website browsing preferences, chatting habits and so on.

The mechanism of Peer-To-Peer Lending

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At times, the concept of Big Data is downright challenging – it creates more confusion than clearing things out. Even Artificial Intelligence is included in this, though marketing teams of countless companies are relying on this advanced technology to enhance profitability and efficiency in operations – pundits from the online lending industry believes AI can actually change the way fintech companies perform.

Artificial Intelligence: Let’s Crack the Myths and Unfold the Future to You – @Dexlabanalytics.

Leveraging AI

For example, Upstart, a California-based Peer-to-Peer online lending company uses the power of AI to process loans. It implements machine learning algorithms to perform underwriting decisions. Machine Learning possesses the ability to analyze and coordinate large chunks of customer data to draw patterns that would remain unnoticed if done manually through human analysts.

According to Upstart, this process eventually works out well for people with limited credit history, lower income level and young borrowers. The company has also initiated an automation of 25% of its less risky loans to keep future prospects in mind.

Another Chicago-based startup Avant is harnessing machine learning to identify fraud – by comparing customer behavior with the initial available data belonging to normal customers, while singling out outliers. They are now planning to extend their services to brick-and-mortar banking structures that are planning to set their foot in the online lending business.

5 Hottest Online Applications Inspired by Artificial Intelligence – @Dexlabanalytics.

Today, digital lending is witnessing a steady growth worldwide, and India is not lagging behind. The perks of introducing machine learning and analytics are evident everywhere, so get yourself charged up and ride on the road of analytics. DexLab Analytics offers excellent big data hadoop certification in delhi ncr. Get enrolled today to experience the best!!

 

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Are You a Student of Statistics? – You must know these 3 things

Are you a student of statistics?

We a premiere statistical and data analysis training institute offering courses on Big Data Hadoop, Business intelligence and Ai. We asked our faculty to tell us the three most important things that every student of elementary statistics should know.

So, let us get on with it:

  1. The notion that statistics is about numbers, is in the context only: statistics involves a rich treasure trove of numeric and graphical representation of displaying data to quantify them also it is very important to be capable of generating graphs along with numbers. But that is not the half part of statistics and the main interesting aspect is related to making the big leap from numbers and graphs to the realistic worldly interpretations. Uncannily statistics also poses to be a fascinating philosophical tension raising the question and healthy skepticism about we believe in and what we do not.
  2. The analysis part is not the most crucial part of a statistical study, the most important part lies with the when, where and how of gathering the data. We must not forget when we enter each number or data, calculate and plot the strategies we build on our understanding, but many a times at the time of interpretation that each every graph, data or number is a product of a fallible machine, be it organic or mechanical. If we are able to take proper care at the stage of sampling and observation we will be able to obtain great dividends at the final stage of interpretation and analysis of all our statistical efforts.
  3. All statistical functions off all kinds of mathematical sciences are based on a two-way communication system. This communication system should be between the statistician and non-statistician end. The main aim of statistical analysis is to put forward important social, public and scientific questions. A good statistician knows how to communicate with the public especially with those who are by and large not statisticians. Also the public here plays an important role and must possess simple idea of statistical conclusions to grasp what the statisticians have to say to them. This is an important criterion to be incorporated in the K-12 and college curriculum for elementary statistical students.

Data Science Machine Learning Certification

If you agree with our views and would like to discuss further on statistics and its application on data analysis then feel free drop by DexLab Analytics and stay updated on the latest trends in data management and mining.

 

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5 Online Sources to Get Basic Hadoop Introduction

Basic Hadoop Courses

Big data Hadoop courses are hitting it big in the world of business whether it is healthcare, manufacturing, media or marketing. Data is generated everywhere, and Hadoop is a readily available open source Apache software program that can be utilized to crunch and store Big Data sets.

As per reports from the Transparency Market Research the forecast shows a promising growth opportunity from the existing USD 1.5 million back in 2012 to USD 20.8 million within 2018. These promising growth numbers suggest that there will be an increased need for human resources to manage, develop and oversee all the Hadoop implementations.

#BigDataIngestion: DexLab Analytics Offers Exclusive 10% Discount for Students This Summer

DexLab Analytics Presents #BigDataIngestion

Many experts believe that one can learn any new subject by simple self-study if only you invest enough time and sincere predisposition towards a topic. After all self-study is actually what a person does to acquire knowledge about any given topic. Be it how to fix a leaky faucet or learn a new language or learn strum a guitar. Studying is on one’s own in any case. But to be an expert in a given field, you have to study on your own while you also need to invest your energy in the right direction. And to know the right direction, you need a mentor or a guide to lead the way.

But if you want to test the waters, and tinker with Hadoop to understand its basics, you can go through the wide range of documents available at the Apache Hadoop website for your perusal. Also try downloading the Hadoop open source release to get the feel of the program while tinkering with different features.

Here are 5 online sources where you can seek some basic introduction to Hadoop for big data:

  1. IBM’s open sources, Hadoop Big Data for the Impatient is a good option to go through the basics of Hadoop. It also offers a free download of Hadoop image (you might need Cloudera) to help you work with examples of Hadoop-based problems. You will also be able to get an idea of Hive, Oozie, Pig and Sqoop. The course is available in Vietnamese, Chinese, Spanish and Portuguese.
  2. Cloudera offers a Cloudera essentials course for Apache Hadoop. Apache Hadoop chapter wise video tutorials are available with Cloudera essentials. But this course is mainly targeted at administrators and those who are well-acquainted with data science, to update their skills on the subject.
  3. YouTube also offers a long list of videos on Hadoop topics for beginners. Some are good while others may not be so helpful for the Hadoop virgins. Simply type Hadoop and you will find a never-ending list of videos related to Hadoop. Some are quite useful for clarifying simple doubts related to Hadoop.
  4. Udemy is another site where you can get some free videos as well as a few for a fee. Simply put Hadoop free on the search bar at their homepage and see what comes up.
  5. Udacity was developed by Silicon Valley giants like FaceBook, Cadence, Twitter and the likes. They offer a 14-day free trial with free course materials. But you will need to pay for the course if you do not finish the course within 14 days.

 

Seeking a good and reliable Hadoop training in Delhi? When DexLab Analytics is here, why look further! Being a recognized Big Data Hadoop institute in Gurgaon, the courses are truly interesting.

 

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Approach – Actionable Analytics

Approach – Actionable Analytics

 

In this blog post, we will discuss on the approach we can follow to provide an actionable analytics. Doing actionable analytics is not easier said than done. It requires a focused analytical process. Here we will outline the three important phase or levers that can improve the process of delivering actionable analytics. The three phases can help you to improve the financial aspects of the business by doing actionable analytics.

 

  • Discover
  • Explore 
  • Engage

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For example, if we are delivering actionable analytics for the marketing function. In each phase we will identify some critical characteristics or parameters that are going to influence the financial value directly or indirectly.

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