Modern Data Ecosystem and the Role of Data Analytics
1. Which emerging technology has made it possible for every enterprise to have access to limitless storage and high-performance computing?
Internet of Things
2. Which of the data roles is responsible for extracting, integrating, and organizing data into data repositories?
Business Intelligence Analyst
3. When you analyze historical data to predict future outcomes what type of Data Analytics are you performing?
1. A modern data ecosystem includes a network of continually evolving entities. It includes:
Data sources, databases, and programming languages
Social media sources, data repositories, and APIs
Data providers, databases, and programming languages
Data sources, enterprise data repository, business stakeholders, and tools, applications, and infrastructure to manage data
2. Data Analysts work within the data ecosystem to:
Gather, clean, mine, and analyze data for deriving insights
Develop and maintain data architectures
Build Machine Learning or Deep Learning models
Provide business intelligence solutions by monitoring data on different business functions
3. When we analyze data in order to understand why an event took place, which of the four types of data analytics are we performing?
4. The first step in the data analysis process is to gain an in-depth understanding of the problem and the desired outcome. What are you seeking answers to at this stage of the data analysis process?
Where you are and where you need to be
The best tools for sourcing data
What will be measured and how it will be measured
The data you need
5. From the provided list, select the three emerging technologies that are shaping today’s data ecosystem.
Machine Language, Cloud Computing, and Internet of Things
Cloud Computing, Machine Learning, and Big Data
Cloud Computing, Internet of Things, and Dashboarding
Big Data, Internet of Things, and Dashboarding
The Data Analyst Role
1. Which of these skills is essential to the role of a Data Analyst?
Deep Learning models
Big Data Engineering
2. What, according to Sivaram Jaladi, goes a long way in lending credibility to your data analysis findings?
Networking with your stakeholders
Sharing your process of arriving at the findings with your stakeholders
Making sure the presentation looks good
Writing good queries
1. Why is proficiency in Statistics an important skill for a Data Analyst?
For creating queries to extract required data
For acquiring data from multiple sources
For identifying patterns and correlations in data
For creating project documentation
2. Which of these is one of the soft skills required to be a successful Data Analyst?
Integrate data coming from multiple sources
Prepare reports and dashboards
Work collaboratively with cross-functional teams
Filter, clean, and standardize data
3. Which of the data analyst functional skills helps research and interpret data, theorize, and make forecasts?
Proficiency in Statistics
4. In “A day in the life of a Data Analyst”, what according to Sivaram Jaladi forms a large part of a Data Analyst’s job?
Interacting with stakeholders
Creating a report
Cleaning and preparing data
5. In “A day in the life of a Data Analyst”, what are some of the data points that were useful in analyzing the use case. (Select all that apply)
Average billing amount of complainants
Serial number of the meters
Age and education details of complainants
Employment history of the complainants