A Guide to Big Data Analytics Using Python

Big Data Mining:

Well, as the word “Big Data” sounds, its meaning is same which means handling lots of data. Data is the essential tool for today’s business site or for web development field as lots of relevant data provides accurate information to the person. For business men, the quality data can improve tool to understand the market model and web developers can take great advantage of the big data. And the whole process of collecting big data from different sources is referred as data mining.

Big data is very useful as single information can’t help anyone. As the set of data comprised of complex mathematical models and boisterous computing power can create insights human beings aren’t capable of producing. The big data is turning out very profitable for the business and the importance of big data is increasing rapidly. But, the main question here arises is that from where to collect the authentic data.

Well, for that social media is becoming first preference of every person nowadays as lot’s of data can be easily obtained from social media platforms like Facebook and Twitter. Among all the other social media platforms Twitter is considered as best for data mining and let’s look ahead for that.

Why is Twitter Data mining better choice?

Twitter is the hub of data. In Twitter, the tweets of people are totally public and can be easily accessible also. Anybody can read each other’s tweets and make data analysis report from it. A business house can read latest 20000 tweets on their company and can easily understand the market response. But seriously that is too boring and difficult task to read each and every tweet on daily basis. But, this data mining can be easily sorted out by using Twitter’s API. So, here we are going to provide ultimate guide for the beginners to collect useful data from Twitter by using Python as a tool.

Guide to Analysis Big Data using Python!

We’ll be using Python 2.7 for these examples. Ideally, you should have an IDE to write this code in. But here we will be using Pycharm to write down one constructive example in front of you all. To connect to Twitter’s API, we will be using a Python library called Tweepy. Well, let me share steps you need to follow in lieu to generate Twitter data.

√ First, you need to get Twitter create a developer account on the Twitter apps site in order to use Twitter API.

√ Then, after creating the developer’s account, you need to go for Tweepy. Tweepy is an excellently supported tool for accessing the Twitter API. It supports Python 2.6, 2.7, 3.3, 3.4, 3.5, and 3.6. There are a couple of different ways to install Tweepy such as Pip or Github.

√ Now that base tools are stepped, you need to authenticate the process. And now Tweepy can be used for coding.

Conclusion:

Well, Twitter is the junction of big data, so it is very useful to adopt Twitter API to understand the mood of folks. If you are intimidated by this process and want to learn more about it, then you should also read more about the Twitter API, Tweepy, and Twitter’s Rate Limiting guidelines.

Send a Message