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MongoDB Basics Part-II

In our previous blog we discussed about few of the basic functions of MQL like .find() , .count() , .pretty() etc. and in this blog we will continue to do the same. At the end of the blog there is a quiz for you to solve, feel free to test your knowledge and wisdom you have gained so far.

Given below is the list of functions that can be used for data wrangling:-

  1. updateOne() :- This function is used to change the current value of a field in a single document.

After changing the database to “sample_geospatial” we want to see what the document looks like? So for that we will use .findOne() function.

Now lets update the field value of “recrd” from ‘ ’ to “abc” where the “feature_type” is ‘Wrecks-Visible’.

Now within the .updateOne() funtion any thing in the first part of { } is the condition on the basis of which we want to update the given document and the second part is the changes which we want to make. Here we are saying that set the value as “abc” in the “recrd” field . In case you wanted to increase the value by a certain number ( assuming that the value is integer or float) you can use “$inc” instead.

2. updateMany() :- This function updates many documents at once based on the condition provided.

3. deleteOne() & deleteMany() :- These functions are used to delete one or many documents based on the given condition or field.

4. Logical Operators :-

“$and” : It is used to match all the conditions.

“$or” : It is used to match any of the conditions.

The first code matches both the conditions i.e. name should be “Wetpaint” and “category_code” should be “web”, whereas the second code matches any one of the conditions i.e. either name should be “Wetpaint” or “Facebook”. Try these codes and see the difference by yourself.

 

So, with that we come to the end of the discussion on the MongoDB Basics. Hopefully it helped you understand the topic, for more information you can also watch the video tutorial attached down this blog. The blog is designed and prepared by Niharika Rai, Analytics Consultant, DexLab Analytics DexLab Analytics offers machine learning courses in Gurgaon. To keep on learning more, follow DexLab Analytics blog.


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Now Navigate Through Risks with Better Data, Improved Analytics

The treasure trove of data can devise new improved ways to mitigate risks.

 
Now Navigate Through Risks with Better Data, Improved Analytics
 

How to reduce the range of risks and better grasp the reins of the business? Though data is being gathered, and pushed through the highly advanced risk analytics tools, how do the risk insurers utilize these insights to boost improved decision-making procedures that affect the business future and potential losses?

Continue reading “Now Navigate Through Risks with Better Data, Improved Analytics”

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

DexLab Analytics brings Market Risk Modelling training to India. Internet has helped people become technology-driven. Digital transformation is evident all around us. No more, gaining knowledge is a task like moving mountains – right from the confinements of your home, you can now get access to a plethora of information and knowledge, thanks to online learning. Several professionals and students are opting for e-learning method of education, owing to its flexibility and ease of access. And India is not lagging behind in this. Several online classes and sessions are being organized by premier data science learning institutes in India, and DexLab Analytics is one of them. 

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

DexLab Analytics is here with an intensive live demo session on Market Risk Modelling Online for free. The online workshop is taking place on 25th October, 2017 from 10:00PM IST onwards, and will solely focus on how Market Risk Analytics has grown to be the new in-demand analytics course for the financial sector. Our in-house trainers will extensively explain the nitty-gritty of MRM, including its importance, major components, and why is it a must-to-have skill for the future. The interested candidates are asked to register as soon as possible by penning down a mail to DexLab Analytics, mentioning they would attend the workshop on the specified date and time.

Continue reading “Here’s All You Need to Know about DexLab Analytics’ Market Risk Modelling Live Demo Session”

Market Risk Analytics: What It is All About

Market Risk Analytics: What It is All About

With time, firms need more efficient, versatile and highly functional analytics tools to address new, complex issues related to market risk. Market risk analytics involve a comprehensive set of integrated, scalable and productive solutions for wide-range risk management across various verticals of asset classes.

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

Why Risk Analytics?

Risk analytics basically help organizations realize the existence of risks lying under business activities – by facilitating enterprises to identify, determine and manage their company risk. In lieu of this, the pressing need for risk analytics is going to increase across industries in the coming few years. New developments, like real-time risk analytics, which is an advanced form of traditional risk analytics process that calculates risk on a real-time basis, are influencing the entire market, while accentuating its mitigating abilities.

DexLab Analytics Introduces Market Risk Analytics and Modelling Online Session – @Dexlabanalytics.

What the Course Offers?

Many top notch education-providing companies are now offering Market Risk Analytics and Modelling online course to better alleviate and handle risks. Increasing needs to address particular risk-induced challenges and excessive focus on the financial market sector is driving the risk analytics market in India. Hence, learning and honing your skills on market risk is indispensable – DexLab Analytics brings Predictive modelling of market risk using SAS to India. The course module will address key issues, like the different types of risks faced by banks, the 1990’s financial crisis, sources and scope of market risk, theoretical probability distributions, volatility forecasting and clustering models, value at Risk Modelling, quantitative models of market risk and description of key financial products.

Some of the most common types of risks that banks are exposed to are Credit risk, Market risk, Operational risk, Liquidity risk, Business risk, Reputational risk, Systemic risk and Moral hazard. All banks need to establish separate risk management departments to manage, monitor and mitigate such high-flying risks. The concept of probability distributions sheds light on investing options – stock returns are expected to be distributed normally, but the reality may vary. They are mostly used in risk management to determine the probability of an event as well as the proportion of losses that it would strike based on a distribution of historical returns. Clustering models is another branch of risk analytics that helps in identifying groups of similar records and marking the records in accordance to the group in which it belongs. These models are also known as unsupervised learning models. Apart from this, other valuable concepts will be addressed during the online live sessions.

Closing Thoughts

Emergence of real time risk analytics is boosting the market of risk analytics. Technology being the driving factor for real-time analysis trades data to the organizations to balance market volatility. Leading service providers are on their quest to design and develop dynamically configurable risk analytics frameworks for clients. And why not, risk analytics boasts of widespread applications, starting from fraud detection to liquidity risk analysis, credit risk management and product portfolio management – various industries are nowadays looking up to market risk analytics, including banking, financial services, government, healthcare, insurance, manufacturing, transportation and logistics, consumer goods and retail, energy and utilities, telecommunication and information technology (IT), media and entertainment, and many others.

Reach us at DexLab Analytics for over-the-top SAS risk management certification course. Their courses are truly remarkable and perfect to take a step into the world of analytics.

 

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To learn more about Data Analyst with Advanced excel course – Enrol Now.
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To learn more about Data Analyst with Market Risk Analytics and Modelling Course – Enrol Now.

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