The demand for big-data experts is growing, which means that there are more opportunities in this field. Despite being a relatively new field of work, professionals are increasingly looking for employment in this field due to its growth aspects.
A big data career can be very lucrative due to the high salaries and other incentives that are offered to professionals. The lack of experience and novelty of the Hadoop or Big Data job positions makes it difficult for recruiters to find the right candidate.
Recommended Reading: Top 50 Big Data Interview Questions & Answers
The recruiters are strict about the skills and expertise of the candidate and can make it difficult for aspirants to be competitive. If you want to be a successful big data professional, it is important to prepare well for your interview.
Big Data Interview Preparation
Big data jobs require more expertise than normal IT jobs. These jobs require more than just theoretical knowledge. You also need to have practical experience with big data tools and concept understanding. As part of your big data interview preparation, it is important to have the relevant training and certifications in this field. To crack big data interviews, you must prepare step-by-step.
This blog will provide guidance on key steps to take in order to prepare for a successful big data interview.
Step 1: Learn the most important tools and technologies
First, you must update your skills with the necessary technologies and tools. Here are the essential skills you should focus on when preparing for your big data interview.
Statistics and Machine Learning
Statistics is a fundamental requirement for data science. Statistics is widely used to crunch large data sets. It is important to understand the basics of statistics such as P value, confidence intervals and the null hypothesis. R is a statistical tool that is widely used in decision making and experiments. Machine learning is a critical skill in the big data ecosystem. Interviews can be made easier by having a good understanding of ensemble methods, nearest neighbors, random forests, and ensemble methods. These techniques are easy to implement in Python. You can use them and gain expertise in data science.
Basic Programming and Software Engineering
It is helpful to be familiar with basic programming languages, statistical programming languages like R, Python, and database languages like SQL. Experience in Java and other programming languages will be a benefit. If you don’t have any experience with dynamic programming, you should learn it. You should have a basic understanding of programming and the ability to use data structures and algorithms. Aspirants will find it helpful to know the runtime and use cases for data structures such as Arrays. Lists. Trees.
For more information on Big data technology tools, please visit our blog Data Scientists Tools to Improve Productivity.
Data Visualization and Data Wrangling
Data scientists can use tools for data visualization like ggplot. These tools will help you coordinate and understand data usage in real applications. It is also important to know how to clean up data. Data Wrangling is a method that identifies corrupt data and shows how to correct it. Data wrangling and data visualization tools are essential for your big data interview preparation.
Management of products requires an understanding of metrics. Data scientists must be product-oriented. This means they need to know the right metrics to analyze and experiment with. From the perspective of the interview, key terms such as retention rates, conversion rates and customer feedback are crucial. A bonus is the ability to use tools such as Storm, Flume, MongoDB and other related tools.
Familiarity with Data
Amazon, Google, eBay, and Facebook have huge data sets that can be analyzed. This is true for online retailers and social media sites. Therefore, recruiters seek out engineers who have professional certifications or have worked with data giants. Many certifications are recognized by the industry, such as Cloudera and Hortonworks. These certifications will prove helpful for new employees.
Also, read: Top 50 Hadoop Interview Questions & Answers
Step 2: Follow Big Data Interview Preparation Strategies
Once you have the skills and knowledge to use big data tools and technologies effectively, it is time to prepare for f