Are you looking to start your career in data analytics? It is important to figure out what you will need to become a successful data analyst. You must know what the role entails and how it differs from others.
We can define data analytics as:
“A process of analyzing raw data to draw actionable and meaningful insights. Businesses use these insights to make smart decisions.”
Data analysts answer particular questions and challenges that apply to the business, like:
- How can the business boost customer retention rates?
- How can the business improve employee satisfaction?
To answer these questions, data analysts collect and extract data from appropriate resources. Then they organize, sort the dataset, and analyze using suitable techniques.
Depending on the questions and type of data, data analysts decide the type of analysis they will perform. But they typically look for patterns and trends. Before presenting results to stakeholders, data analysts visualize them in the form of charts and graphs. At last, they make recommendations regarding the upcoming steps of the company. These recommendations reflect what the data tells.
Big Data Analytics
Big data analytics is a complex process. It examines big data to reveal information like:
- Customer preferences,
- Hidden patterns, and
- Market trends.
It can help businesses in informed decision-making. Data analytics techniques and technologies also assist businesses in analyzing data sets. In this way, they can gather new information. Moreover, BI answers fundamental questions regarding business performance and operations.
Being the form of advanced analytics, big data analytics involves complex applications. It includes elements like:
- Predictive models
- Statistical algorithms
- What-if analysis powered by analytics systems.
11 Most Asked Big Data Analytics Questions In Apple Interviews
During Apple interviews, there are many big data questions that recruiters ask. An ambitious data analyst at Apple should have a vast knowledge of big data analytics. Recruiters also expect candidates to have experience in managing data through data analytical tools. This can help you to answer interview questions at Apple related to big data analytics.
We have compiled a list of the top 10 big data analytics questions asked in Apple Interviews:
- Explain the meaning and calculation of ACF and PACF.
- Describe the process of how XGBoost manages the bias-variance trade-off?
- Mention the function to detect if a binary tree is a mirror image on the right and left sub-trees.
- Explain the differences between HDFS and YARN with their respective components.
- Mention the five Vs of big data analytics with proper explanation.
- Define characteristics of some important big data analytics tools used in a tech company.
- Are Hadoop and big data related? Briefly explain.
- What are different file formats to be used in Hadoop?
- Explain the goal of A/B Testing.
- What are the differences between HDFS Block and Input Split?
To help you with your interview, here we have some answers to the above-mentioned questions. These answers can help you ace the interviews at Apple:
Answer For Q4: HDFS Vs. YARN
HDFS (Hadoop Distributed File System) is famous because it is highly fault-tolerant. It also grants file permissions and provides authentications. There are three fundamental elements in HDFS:
- Secondary NameNode
On the other hand, YARN (Yet Another Resource Negotiator) is an essential part of Hadoop 2.0. For many data processing engines, businesses use YARN as the resource management layer of Hadoop. There are two fundamental elements in YARN:
Answer For Q5: Five Vs Of Big Data Analytics
The 5 Vs of big data analytics are:
- Variety (many forms of data)
- Volume (data at rest)
- Velocity (data at motion)
- Veracity (data in doubt)
Answer For Q8: Different File Formats Used In Hadoop
There are many different file formats of Hadoop, including:
- Parquet file
- Sequence files
Answer For Q9: The Goal Of A/B Testing
This question requires clear knowledge of A/B testing. The employers present two or more forms of a page before you. You have to observe each variant’s performance.
Key Challenges Of Managing Big Data In The Cloud
Big data analytics has many challenges that analysts face in managing cloud data. We have listed a few challenges below:
Cloud Depends On Network
Cloud needs a continuous supply of internet for uninterrupted services. An outage of internet services at your place can cause connectivity issues. Traditionally, you might not face these types of issues in using big data.
Failure in internet connection leads to loss of access to big data. Any lag in connectivity can also affect the productivity of the team and workflow.
Moreover, your cloud network providers also have sound connectivity to the internet. If they face any such issue, it will affect your work as it will lock you out of the cloud.
If there are mistakes in cloud configurations, it can lead to major weaknesses in cloud infrastructure. These weaknesses become the main cause of cyberattacks that cause cloud breaches.
Cloud migrations are one of the causes of misconfiguration. But, disruptions can appear due to the constant change in the cloud environment. It is difficult to spot errors, mistakes, and glitches during cloud configuration. However, these misconfigurations can cause a higher security risk. It is because they leave behind weaknesses in the cloud that cybercriminals can manipulate.
Sticking to Compliance Standards
When you manage big data in the cloud, it introduces you to differences in compliances standards. Compliance standards vary from country to country. Organizations using the cloud have to get certified for necessary compliance standards.
If you are not aware of the compliance standards governed by nations around the globe, you can get into violations. It has to be the biggest concern when you are migrating to the cloud.
DDoS Attacks on The Cloud
DDoS (Distributed Denial of Service) Attacks overburden the cloud with fake traffic. This makes it too slow or even stops it from working as a whole.
This type of cyberattack can:
- Diable your data backup,
- Affect your productivity,
- Create duplicate copies of your files, and
- Cause data storage to be disorganized or overwhelmed.
DDoS attacks are difficult to spot. This is the main problem of these cyberattacks. It means that the organization will not be able to mitigate the threat at the right time. This can cause a delay in your work.