Analytics Jobs
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Reviews Dekha Kya - Analytics Jobs

Analytics Jobs is India’s first EdTech platform in the Questions and Answers category. The platform is designed to provide a space for learners and alumni from various educational technology institutions to rate, review, and discuss tech courses offered by these institutions. Analytics Jobs allows users to share their experiences with specific courses, detailing how the course has impacted their careers and whether they recommend it to others. We bring together alumni, current learners, future learners, and educational technology institutions on a single platform.

Analytics Jobs
  • 4
Review
Analytics JobsEnlightened
Asked: July 11, 2022In: Data Science & AI
  • 4
Scaler Academy Reviews – Career Tracks, Courses, Learning Mode, Fee, Reviews, Ratings and Feedback – 2024

Poll Results

12.35%Successfully Got a Job Offer ( 10 voters )
16.05%Satisfied ( 13 voters )
29.63%Not Satisfied ( 24 voters )
41.98%Worse ( 34 voters )
Based On 81 Votes

Participate in Poll, Choose Your Answer.

  1. Prince
    Prince

    I have enrolled in scaler data science course recently. And after completing a couple of months studies with them here are the Pros and Cons for me: Pros: Very structured course and relevant topics. Along with really good assignments after each class. Instructors are really good. Until now I have onRead more

    I have enrolled in scaler data science course recently. And after completing a couple of months studies with them here are the Pros and Cons for me:

    Pros:

    1. Very structured course and relevant topics. Along with really good assignments after each class.
    2. Instructors are really good. Until now I have only interacted with Mohit Uniyal, and I think he is really good. He is very thorough and amazingly patient while answering doubts.
    3. Teaching Assistance support is another great resource. You can reach out to them anytime via chat or video call. So that’s very handy.
    4. The dashboard is laid out really well too. The options to view class recordings any time, making bookmarks, discussion, scaler support access. Very neat!
    5. I have heard they have good placement and career support as well. I haven’t availed or experience this yet first hand since I am only 2 months in the course now.

    Cons:

    1. Quite expensive course for sure, but given the quality and other equally and more expensive courses in the market such as upgrad, I am not surprised.
    2. Features like mentors are not very helpful, as even many mentors are still figuring out their career.
    3. A lot of spam from scaler. OMG! like you name it, Email, Whatsapp, Slack, so much spam from scaler and other learners.
    4. Lack of quality network building. Eventhough scaler has the above platforms where learners can connect, it still fails to help learners network. I know it is a hard thing, but I hope scaler can come with something where learners can benefit from each other.

    Fell free to each out to me on LinkedIn if you have any other questions – https://www.linkedin.com/in/-prince-jindal/

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Anonymous
  • 0
Review
Anonymous
Asked: September 2, 2022In: Data Science & AI
  • 0
Praxis Data Science Course Reviews – Career Tracks, Courses, Learning Mode, Fee, Reviews, Ratings and Feedback

Poll Results

0%Successfully Got a Job Offer ( 0 voters )
33.33%Satisfied ( 1 voter )
0%Not Satisfied ( 0 voters )
66.67%Worst ( 2 voters )
Based On 3 Votes

Participate in Poll, Choose Your Answer.

  1. Sohasani Vasu
    Sohasani Vasu

    As a former Data Science student at Praxis Business School, I thought the placement services offered here were really great. The college has more to offer than only a well-organized infrastructure, highly skilled lecturers, and cutting-edge facilities. The on-campus hiring procedure is excellent. ThRead more

    As a former Data Science student at Praxis Business School, I thought the placement services offered here were really great. The college has more to offer than only a well-organized infrastructure, highly skilled lecturers, and cutting-edge facilities. The on-campus hiring procedure is excellent. The committed faculty helps the students in any way they can by offering advice, holding training sessions, and coaching them continuously. I might add that I was a little hesitant to enroll in this college prior as well. I made the decision to meet a few seniors I had previously known in order to learn more about the placement services and to get any questions I had answered.

    Within the college grounds, there is a separate wing dedicated to career counseling. Outstanding training facilities are made available to the kids, which I believe is crucial for their future. My seniors informed me that the counseling department helps students find their talents and shortcomings while guiding them. They get the confidence necessary by the time they encounter the recruiters. To evaluate the students’ performances, a number of training sessions are held, including PowerPoint presentations, group discussions, and open-ended question and answer sessions. This not only aids in preparing them for the interview but also develops their job readiness. We are urged to participate in such events from the first day of our course, which increases our opportunities.
    Placement is generally good. The course load is demanding. It is a demanding one-year course. Prior to enrolling in this course, have some programming experience.

    Work hard and you’ll be rewarded. From this place, I am learning so much. The course is the ideal blend of practical and academic learning. Our programme includes everything, from application-based learning to thorough analytics to practical laboratory experience. All of the mentoring and direction offered by our counseling divisions is of a high caliber. These sessions are not only extraordinary, but they also really help us. We are also given the opportunity to participate in internship programmes to gain practical experience. Additionally, some of the most coveted employers, like IBM, Tata Consultancy Services, and ICICI, hired our seniors.

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    • 1
Analytics Jobs
  • 0
Review
Analytics JobsEnlightened
Asked: September 11, 2023In: Data Science & AI
  • 0
Skillslash Reviews – Career Tracks, Courses, Learning Mode, Fee, Reviews, Effective Ratings and Feedback

Poll Results

4.55%Successfully Got a Job Offer ( 1 voter )
13.64%Satisfied ( 3 voters )
22.73%Not Satisfied ( 5 voters )
59.09%Worse ( 13 voters )
Based On 22 Votes

Participate in Poll, Choose Your Answer.

  1. Anonymous
    Anonymous

    Attention all students! I feel it is my duty to warn you about a concerning experience that my friend had with SkillSlash, an online course provider. This company has been using deceptive tactics to attract students, claiming to offer demo classes and a money-back guarantee if you are not satisfied.Read more

    Attention all students! I feel it is my duty to warn you about a concerning experience that my friend had with SkillSlash, an online course provider. This company has been using deceptive tactics to attract students, claiming to offer demo classes and a money-back guarantee if you are not satisfied. However, my friend fell victim to their false promises when she was unable to attend the demo class due to legitimate reasons. It has now been a month since she requested a refund, but the company has failed to fulfill their promise.

    Furthermore, my friend was shocked when their finance team attempted to pressure her into paying the full course fee of 1 lakh rupees immediately after the demo class. Thankfully, she was smart enough to refuse this request and avoid being scammed out of her hard-earned money. It is alarming that SkillSlash would resort to such unethical tactics in order to make a profit.

    I urge all students to be cautious and vigilant when considering online courses from this company or any others that operate similarly.

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Dhakad Singh
  • 0
Dhakad SinghBeginner
Asked: November 7, 2022In: Data Science & AI
  • 0
  1. Kapil Rai
    Kapil Rai
    This answer was edited.

    Data analytics is the regularly intricate interaction of analyzing huge information to uncover data like secret examples, connections, market patterns and client inclinations - that can help associations settle on educated business choices. Data analytics is a type of cutting edge analytics, which iRead more

    Data analytics is the regularly intricate interaction of analyzing huge information to uncover data like secret examples, connections, market patterns and client inclinations – that can help associations settle on educated business choices.
    Data analytics is a type of cutting edge analytics, which include complex applications with components like prescient models, measurable calculations and consider the possibility that examination is fueled by examination frameworks.
    There are 4 types of data analytics majorly used and they are as follows

    1.Descriptive Analytics -It is the basic among the 4 types of data analytics. It is used to understand the overall performance at an aggregate level and is by far the easiest place for a company to start as data tends to be readily available to build applications and reports. It’s very important to build core competencies first in descriptive analytics before attempting to advance upward in the data analytics maturity model. It is the first pillar of analytics, descriptive analytics also tend to be where most organizations stop in the analytics maturity model.

    2.Diagnostic Analytics- It, just like descriptive analytics, uses historical data to answer a question. Diagnostic analytics happens to be more accessible and fits a wider gap of use cases than predictive analytics or machine learning.

    3.Predictive Analytics- It is a form of advanced analytics that determines what is likely to happen based on previous data using machine learning. Historical data that comprises a bunch of descriptive and diagnostic analytics is used as the basis of building predictive analytics models.
    While modeling takes up the main point in predictive analytics, data preparation is a crucial step that needs to happen prior to that. This is why organizations with a solid foundation in descriptive and diagnostic analytics are better and effective at handling predictive analytics.

    4.Prescriptive analytics- It is the 4th, and final pillar of modern analytics. Prescriptive analytics becomes true guided analytics where your analytics is prescribing or guiding you towards a specific action to take. It is the combination of descriptive and predictive analytics to drive decision making. It is the last yet one of the most important among the 4 types of data analytics.

    These are the 4 types of data analytics and this will give you a better insight about data analytics.

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RP Singh
  • 1
RP SinghBeginner
Asked: November 4, 2022In: Data Science & AI
  • 1
  1. Mayank Newar
    Mayank Newar

    When it comes to the interview part there are a lot of questions which are generally asked. The data analyst technical interview questions differ from one angle to another. I have sorted from a bundle of questions and will share with you some of the most important data analyst technical interview quRead more

    When it comes to the interview part there are a lot of questions which are generally asked. The data analyst technical interview questions differ from one angle to another. I have sorted from a bundle of questions and will share with you some of the most important data analyst technical interview questions. you will get a rough idea of what type of data analyst technical interview questions will be asked for your interview.
    1. Name the best tool for data analysis? Candidates with good practical knowledge are the only ones to excel in this question. So make sure that you have different practice tools and analytics questions for your analyst interview and data analyst behavioral interview questions. Well! here some of the best tools for data analysis KNIME, Solver, NodeXL etc.
    2.What are the different data validation methods used by data analysts? One of the frequently asked data analyst technical interview questions
    Field Level Validation- It helps to correct the errors as you proceed
    Form Level Validation- It checks the entire data entry form at once, validates all the fields in it, and highlights the errors so that the user can correct it.
    Data Saving Validation- Usually, it is done when multiple data entry forms must be validated.
    Search Criteria Validation- The main idea of this validation method is to ensure that the user’s search queries can return to the most relevant results.
    3. What are the key requirements for becoming a Data Analyst? This is one of the most important data analyst technical interview questions.
    You should have substantial technical knowledge in fields like database design, data mining, and segmentation techniques.
    4. What is the meaning of data cleansing? Data cleansing basically means to the process of detecting and removing errors from the data to improve data quality. Although containing valuable information, an unstructured database is hard to move through and find valuable information. Data cleansing simplifies this process by modifying unorganized data to keep it intact, precise, and useful.
    5. What is time series analysis? This brings the structure to how the analysts record the data, instead of going ahead observing the data points randomly, they observe data over set intervals of time. It is used for nonstationary data, data that is dynamic and constantly moving. It has applications in various industries such as finance, retail, economics, etc.

    These are some of the frequently asked data analyst technical interview questions.

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Rishi Jaat
  • 1
Rishi JaatBeginner
Asked: November 5, 2022In: Data Science & AI
  • 1
  1. Shahid shekhawat
    Shahid shekhawat

    Nowadays, Data Science and Artificial Intelligence are the two most important technologies. In contrast, Data Science uses Artificial Intelligence in its operations. Data Science and Artificial Intelligence are used correspondently. Data Science may come up with some aspects of AI but does not refleRead more

    Nowadays, Data Science and Artificial Intelligence are the two most important technologies. In contrast, Data Science uses Artificial Intelligence in its operations.
    Data Science and Artificial Intelligence are used correspondently. Data Science may come up with some aspects of AI but does not reflect it. Data Science is the current ruling technology that has conquered industries worldwide. It brought the fourth industrial revolution to the world today.
    Data Science involves various fields like Statistics, Mathematics, and Programming. So, a data scientist must be proficient in understanding data trends and patterns.
    For doing a data science course, you don’t need to be from a technical background. So if you want a better career opportunity go for it. Data Science courses are budget-friendly, and many institutes provide Data Science courses with affordable fee structures. Nowadays, data science has a high demand in all domains. So, rather than taking a high payable course, you can take a data science course.
    Artificial Intelligence is the Intelligence technique that is possessed by machines. It is modeled after the natural Intelligence possessed by animals and humans. Artificial Intelligence makes use of algorithms to perform autonomous actions.
    Artificial Intelligence also uses several software engineering principles to develop solutions to existing problems.
    For AI, you must have programming knowledge. It is more technical than a data science course. A course in AI is much costlier than a Data Science course.
    1. Data Science is a long process that involves processing, visualization, analysis, and predictions. On the other hand, AI is the execution of a predictive model to predict future events.
    2. Data Science comprises various statistical techniques, whereas AI uses computer algorithms.
    3. Data Science involved more tools than in AI because Data Science involves multiple steps to analyze data and generate perceptions.
    4. Data Science is all about finding hidden patterns in the data. AI is about relating autonomy to the data model.
    5. Data Science is for build models that use statistical perceptions. In contrast, AI is for building models that reproduce cognition and human understanding.
    6. AI involve a high degree of scientific processing as compared to Data Science.

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Sukesh Dahiya
  • 2
Sukesh DahiyaBeginner
Asked: November 5, 2022In: Data Science & AI
  • 2
  1. Dolly Singh
    Dolly Singh
    This answer was edited.

    Both of these two roles have tremendous scope in the world today. The difference between bi analyst and a data analyst is not much but there are a few factors which distinguish them one from the other. I will share with you my view on the difference between bi analyst and a data analyst. Business inRead more

    Both of these two roles have tremendous scope in the world today.
    The difference between bi analyst and a data analyst is not much but there are a few factors which distinguish them one from the other. I will share with you my view on the difference between bi analyst and a data analyst.

    Business intelligence analysts (BIAs) examine and analyze data, often using software tools to identify trends or patterns that might otherwise be overlooked. For example, a BIA may uncover a pattern of customers who have recently bought a product but returned it because they were dissatisfied with the color. As another example, an analyst could use data collected from consumer surveys and sales numbers to predict a future product trend. Business intelligence analysts often work with huge amounts of data, so they must be comfortable working with computers and using them to organize and analyze information for their employers. BIAs also use software tools that help them find trends in the data or visually depict patterns.

    Business intelligence analysts can find employment with a wide variety of employers. They work for businesses in almost every industry, including retail, banking, manufacturing, and healthcare. Some analysts work as consultants who travel to various locations to evaluate data and make recommendations based on what they find. Many analysts also have careers at colleges and universities where they work with administrators to collect important data related to the school’s financial health and other matters.

    When it comes to data analysts. A data analyst is responsible for maintaining and designing databases and systems for various departments, creating dashboards, programming, using tools like Tableau and business intelligence software. Most data analysts collaborate with management, IT teams, or data scientists to gather or clean data for business insights or uncovering trends. The data analysts job description may include presenting data in charts, tables, graphs designing and developing relatable databases for collecting data and in some companies it also includes designing and building data input or data collection screens.

    There are no major differences between these two roles but a slight difference exists. So, These are some of the differences between bi analyst and data analyst.

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