Data science is one of the emerging fields of today that has proven its worth with its multidimensional scope using a realm of scientific methods. The reason why it’s so prominent is because it encompasses the use of various subjects and focuses on emerging trends by analyzing data.
If you’re an enthusiast and someone looking to explore the domain, then you need to be aware of the data science tools that will help you excel. Since the domain works with big data, using these tools is important and will surely aid in your career. So, let’s check these out now:
Semantria
What this tool does is nothing less than magic! Semantria is a high-end Neuro-Linguistic Programming (NLP) tool that uses an element-based detection method. This method allows it to analyze data through texts and even through sentiments.
In other words, the tool makes it easier to collect and analyze data even if it’s not in text form. If you’re working with such kind of data or viewing it from a different source, then using Semantria will be highly useful.
Trackur
Another amazing tool that data scientists should be familiar with is Trackur. This tool makes it easier to collect data from brands and products. However, it allows tracking from social media platforms as well as allows analysts to strategize for their marketing campaigns.
However, you’ll need to have smooth internet running to ensure that the data collection process isn’t interrupted. For that, we recommend seeking help from xfinity customer service since it’s known to offer good speed with reliable connectivity. Simply, connect with its customer services and get a plan right away.
Apache Hadoop
Apart from data collection tools, you also have data storage tools that are designed to collect huge volumes of data, storing them effectively for use later. Apache Hadoop is one of the prominent names in the market when it comes to data storage tools.
The tool operates using a framework that offers a layered structure for data distribution. These tools operate using this framework for data storage and computation. The layered structure allows storing data amongst clusters of computers that are connected to the primary hub.
This clustering of data-storing computers makes it easier to process large volumes of data without any interruption. Hence, if you’re a data scientist going deep into data analysis, you’ll need one such tool for your journey.
Mongo DB
Another competitive big data storage tool in the market is Mongo DB. Mongo DB is document-oriented and uses a database-like module for storing, retrieving, and analyzing the data. It’s also easily available for platforms, including Windows, Solaris, and Linux.
OctoParse
When it comes to collecting data from online platforms, you’ll need a data extraction tool that will allow you to extract the sourced data and represent it as you require on your workstation. These extraction tools work alongside the data collection tool, making it easier to collect and sort data.
OctoParse is a great example of a data extraction tool that allows data scientists to extra data in a readable format. It does so by giving the output in a structured spreadsheet. With this web-scraping tool, users can easily obtain data in a required format and use it for further purposes such as extracting phone numbers, IP addresses, emails, etc.
Content Grabber
Another example of a web scraping tool that allows the same functionality as the tool given above. However, it’s an advanced tool that even allows debugging and error handling. In addition, the striking element of this tool is that it allows data extraction from almost every website.
Moreover, it can also provide structured data as an output that the users can adjust as per preferences. Doing so makes it easier to obtain data in any readable format and utilize it further.
OpenRefine
While data scientists are collecting large volumes of data, there’s a great chance that trash or junk data is also collected. That is why there’s a great need for data cleanup tools to minimize this problem. OpenRefine is a competitive choice for this purpose that one can count on.
OpenRefine comes with great refining features that are targeted towards minimizing data junk. It enables the users to transform the data into something useful, cleaning and untangling it and providing data access with speed and easiness.
In other words, you can use a data extraction tool and then use a data cleaning tool, which will sort and clean the data for easy usage.
Closing Thoughts
When it comes to becoming a successful data scientist, you should equip yourself with the right tools so that you can get the maximum output. The abovementioned ones are some instances that you can go with. You can also research different alternatives to the ones mentioned so that you can find the right ones.
