Answer :

Part 1

a. The online streaming (media) industry

As of 2020, the global video streaming or online streaming market was valued in excess of US$50 billion with an extremely high anticipated compounded annual growth rate of almost 21% for the period of next 8-10 years. New innovations such as blockchain technology and AI are expected to further boost the growth. AI already has widespread use in order to provide better quality content to the viewers. The use of cloud-based technologies also has a positive impact on the growth. Apart from streaming television, online games and education services also form important segments of the market. Particularly, the growth has been rampant in the COVID-19 era.

Particularly, the major rivals in the market include YouTube, Netflix etc. Continuously, new players are entering the market such as Google with Yeti game streaming services, Apple Inc. for online video cascading industry, Amazon’s Fire TV etc. (Grand View Research, 2021).

The major barrier to entry to the market is content creation or acquisition along with the licensing procedures. Another technical barrier is to have appropriate capacity so as to ensure smooth streaming and minimal crashing of the platform due to heavy traffic.

b. Netflix competitive strategy

One of the major competitive advantage for Netflix is having quality content across genres. It is identified as a high-quality entertainment platform as it makes big investments in creating or acquiring good content. It has a large number of original shows. Another big advantage is its simple and easy to navigate platform that works as efficiently and smoothly across variety of devices, be it television, laptop, mobile or a tablet. Hence, the user experience is highly positive (Bylund, 2018).

The key strategy is to provide positive user experience in terms of content as well as simplicity. 

c. Purpose of implementing big data analytics 

Data analytics simply means analysing available data. However, the important thing is to analyse the given data to reach the stated goal in most efficient manner. Hence, for example, for a streaming company one of the important uses of data analytics will be to provide relevant content according to a user’s tastes and preferences so as to provide a good user experience. Hence, it may involve multiple parameters such as user watching history, demographics, age etc.

Hence, the main purpose of big data analytics is to provide better experience to the users with respect to accuracy, reliability, convenience etc.

Part 2
d. Data-driven company’s characteristics

A data-driven company, such as Netflix, is a company that knows the importance of data and uses data analytics techniques in order to provide better products and services. Data forms the foundation of all the business decisions so as to get better operational and financial efficiency. The main characteristics of such companies are (Peregud, 2018):

1. Open-minded culture that encourages free thinking and creativity: This is important so as to enable members to contribute positively and think out of the box. The motivation and passion leads people to work responsibly.
2. Easy access to data to all the members of the organization: This is a pre-requisite in a data-driven business so as to make accurate and quick decisions at various levels.
3. Data Literacy: In order to be able to navigate through the data, it is necessary that the members have the skill and knowledge to be able to read, analyze and work with the data effectively.

e. Business intelligence and data analytics

The terms are very similar but while business intelligence refers to use of techniques and analyzed data so as to take business decisions and form strategies, data analytics refers to the analysis of data so as to achieve a set goal. While business intelligence focuses on past and present, data analytics focuses on the future (Durcevic, 2018).

f. Benefits by implementing big data analytics

The big data analytics implementation must lead to predictive analysis through gathered data, lower the costs and save time by weeding out irrelevant data and help in bettering the user experience. 

Part 3

g. Structured and unstructured data

As the name suggests, structured data is a data that can be processed, stored or retrieved in a particular format. Hence, the data is highly organized, for example employee details. The data cannot be changed easily as the structure is set.

Unstructured data refers to the data that lacks a particular format or structure and may vary from point to point. For example, emails. It is difficult to navigate the data and analyze so as to achieve output.

Netflix is more likely to collect unstructured data such as videos, audios, emails, text files etc.

h. Benefits of a cloud-based application

Typically, a cloud-based application is:

1. Cheaper: saves on hardware and maintenance cost that would have been required otherwise. The capital expenditure is minimal.
2. Already available infrastructure and application: This leads to more focus on the business work rather than setting up the infrastructure or application itself. 
3. More productive: The easy access to information and data at any given point of time leads to quicker and more efficient decision-making processes.

i. Main obstacles/challenges

The main challenges for ‘big data analytics’ include (Sharma, 2020):

1. Lack of data understanding: Typically, the companies fail due to lack of knowledge and understanding about data and handling it properly. The data professionals may help and do handholding in the beginning. However, ultimately, it is the company employees who have to run the show. If these employees are not well-versed in understanding and working with big data, the mission falls flat.
2. Immense data volume handling: With time, the data to be stored grows exponentially. Given that the data will be unstructured in nature. Hence, it gets difficult to store the data in an organized manner and worse, navigating or using the stored data at the right time gets overwhelming.  
3. Data Security: While it can be seen that company entering big data analytics will be overwhelmed with understanding and working with big data, it is equally important to pay attention to investing in securing the data so as to avoid hacking of data. However, a new company may be so overwhelmed or engrossed in handling data that this becomes a low priority and may lead to failure.

Part 4

j. Netflix challenge in 2014

Netflix was launched in France but was challenging due to sceptical public. They used a ‘Data Driven GIF Campaign’ in order to connect with the French people’s daily problems and solutions. They were able to get into French minds and crack the market with increased user base and high brand awareness.

k. Types of data in the “Data Driven Gif Campaign” 

Topics model which is natural language processing system that helps to identify insights that can be converted to business opportunities. The irrelevant data referred to as the surface and noise was removed so as to get the insights.

l. The most important feature

The recommendation system that puts out the recommendations lines for user is very important as 80% of the content watched is from these recommendations. It is based on A/B testing method used by the company. Hence, it is a very big lever for Netflix.

m. Personal information from its users

The personal information of the user collected by Netflix is far more intense and deep as compared to information gathered by other marketing techniques. Hence, the profiles created are very detailed on the basis of various data points, including customer interactions and response to a TV show.

Although mentioned in privacy policy etc., it still borders on being unethical and may be invasion of privacy.