Data science feeds on data. Data from everywhere is gathered, processed, analyzed and ultimately used to draw conclusions and make decisions accordingly. Thanks to data science, almost all the industries are benefiting from it. Which makes the job of a data scientist crucial, as it’s him/her who is going to manage through all the intricacies of the data. The tasks are as overwhelming as they sound and that’s why data science tools exist to make things easier. With the rising development and need of data science, there’s an emergence of 2 types of data science tools:
- Self-service tools for those with technical skills, i.e., got programming skills and know statistics & computer science.
- Tools for business users which automate the commonly used analysis.
Popular tools for people with technical skills
As per various surveys, the most popular tools used by data scientists these years are Python, R, SQL, C++, Java, C, JavaScript, MATLAB and others. Out of these, it is python that’s been gaining popularity over the years. It is the most used, followed by SQL & R.
- Python has free data analysis libraries
- It is extensible
- It has a number of free useful packages used by data scientists.
Therefore mastering python first by joining a python certification course would be a wise step. Thereafter you can move on to others which you’ll have to as you’ll never get enough tools.
Data science tools for everyone
SAS
It’s an integrated software suite for statistical analysis, advanced analytics, econometrics, time series analysis, BI and data management. You can perform granular analysis from textual data and generate insightful reports.
- Easy to learn & use
- Simple & powerful GUI
- Dedicated technical support
- Visually attractive reports
- Detects spelling & grammar errors for accuracy of reports
- SAS supports mining, alteration, managing & retrieval of data from different areas. SAS & SQL together make an efficient tool for data access & analysis.
Tableau
Tableau is a data visualisation tool where even advanced data is represented quickly visually for ease of understanding by everyone and thereby in making quick decisions. It works by using online analytical processing cubes, cloud databases, spreadsheets & relational databases. You just need to concern yourself with the statistics and get started by dragging & dropping a dataset onto the application and set up filters for customization.
- Comprehensive end-to-end analysis
- Advanced data calculations
- Negligible security risks
- Responsive user interfaces that fit on all screen types & sizes.
Apache Hadoop
It is an open-source software. It facilitates solving complex computational problems & data intensive tasks by using parallel processing across clusters of nodes. Hadoop accomplishes this by breaking large files into chunks and sending them to nodes along with instructions.
Components of Hadoop that increase its efficiency & processing:
- Hadoop common contains standard libraries & functions for the subsystems
- Hadoop distributed file system offers file system & mechanism to split & distribute chunks
- Hadoop YARN handles job scheduling & management of chunks
- Hadoop MapReduce manages parallel processing
- Disk-powered projects are sped-up by 10 times-per-project
- Seamless integration with external apps & software solutions.
A good data analytics course will definitely introduce you to apache software.
TensorFlow
TensorFlow library supports building & training models, deployment on diverse platforms (computers, smartphones, and servers) and achieving maximum potential with finite resources. You can create statistical models, data visualisations and access widely used features of ML & DL. TensorFlow with python is used to operate with numbers & data by storing, filtering & manipulating them for distributed numerical computations. Whichever data analyst course you join, make sure they teach you TensorFlow because of its uses in AI, DL & ML.
London School of Emerging Technologies
There are indeed even more data science tools that aid the job of the data scientist efficiently but these are among the top. Anyway, no data scientist ever said “I’ve enough tools.” The way AI has gripped today’s world, it goes without saying that a data scientist has a crucial role to play in a company’s success. If you’ve knack for data science, you need to get the right tools and knowledge with which LSET can help. We have separate java & python certification courses, machine learning and data science. Our data analyst course covers all the relevant tools and helps you make a strong base to learn others with ease.