Gospel truth:
There are as many chunks of digital data as there are stars in the universe.
Some key facts about Data Analysis:
- The Data Science analytics market is expected to grow eightfold and will reach around USD 16 billion, by 2025.
- Around 60k search queries are made on Google every second, which reaches a whopping 1.2 trillion searches every year.
- Around 1000 computers are used by Google to answer every single search query.
- The data created by individuals across the globe is 70%, out of which 80% is stored and managed by the enterprises.
- Bad data costs USD 600 billion every year in the US alone.
- Data Scientists are professionals who earn more than the average IT employees.
- There will be 700,000 new data jobs by 2020 across almost all industries, according to IBM.
According to Srikanth Velmakanni, CEO of Fractal Analytics, “there are two types of talent deficits: Data Scientists, who can perform data analytics, and Analytics Consultants, who can understand and use data. The talent supply for these job titles, especially data scientists is extremely scarce, and the demand is huge.”
These are the reasons why many professionals are moving towards learning data analytics to make a career in this ever-growing domain. Data analytics is used today in each and every company, regardless of its type, size, and geographic location. Let’s explore data analytics for beginners and how they can learn it.
What is Data Analytics?
Simply put, the science of analyzing raw data is referred to as data analytics. The data is analyzed to draw useful insights from the raw data which may be structured, unstructured, or semi-structured. The traditional methods of data analysis are not so efficient enough to analyze such massive amounts of data that is generated from the activities we perform on our smart gadgets.
Today most of the processes and techniques involved in data analysis are automated into algorithms and mechanical processes that process raw data to enhance the efficiency of a system or a business.
Data analytics techniques are so designed that they disclose metrics, patterns, correlations, aberrations, and trends that would have been lost in the bunch of information. Generally, the information obtained is useful in one or the other way to make our business work efficiently.
Steps involved in data analysis
- The first step is to sieve or separate the data into groups which may be divided by considering relevant factors such as age, name, gender, income, demographics, or any such factors.
- Data is collected from various resources such as social media posts, online sources, computers, environmental factors, or even personally.
- Then the data is organized in a Spreadsheet or any such application that takes statistical data so that it can be analyzed.
- Before analysis, the data is cleaned, scrubbed, and examined for any errors, duplicates, or incomplete data. This step prepares the data entirely so that it can be analyzed in a trouble-free process.
Skills Required to Become a Data Analyst
To become a successful data analyst, there are some skills you need to master so that you can use the tools and techniques involved in data analysis efficiently.
Programming Languages
R and Python are the most common programming languages used by data analysts. Other languages that are widely used in data analysis include Java, MATLAB, SAS, Scala, Julia, TensorFlow, and SQL. Basically, the programming languages are selected on the basis of whether the compilation is to be done before running and is divided into two categories: statistical and scripting.
Data Processing Platforms
Today, data analysts use large data processing platforms such as Hadoop and Apache Spark so as to analyze massive datasets. These platforms let you query the data across multiple devices, model and explain it so that you can extract meaningful insights from it.
Math
In data analysis, you need to perform statistical methods, and so you are required to have a basic knowledge of math. While there are powerful scripting languages like R to handle large datasets, statistical capabilities as in Microsoft Excel let you manage smaller datasets.
Machine Learning
For large scale data analysis, automation is at the core. Machine learning algorithms help computers to automatically learn and perform tasks without the requirement of explicit programming. As a data analyst, you are expected to know how to create, implement, and train the appropriate models and algorithms to datasets so that the right solutions are identified for specific problems.
Data Visualization
When you have extracted meaningful insights, it is crucial to present it in some meaningful format so that it becomes easy to understand for users reading it. One of the most widely used data visualization tools today is Tableau, which enables you to query the data stored in the cloud and relational databases, online analytical processing arrays(OLAP), and spreadsheets to generate a graphical representation of the insights extracted.
Apart from the hard skills listed above, you need to acquire some soft skills that are crucial for you to learn data analysis. The first and foremost soft skill required is excellent communication and presentation skills so that you can share your findings with potential business partners effectively.
To become a successful data analyst, you need to take a systematic and logical approach to problem-solving. So you have to develop critical thinking capabilities and creativity to perform data analysis so that you can identify vague connections and find out meaningful insights.
In addition, you should be adaptable and adjust to a variety of teams to meet the business requirements by using database intelligence.
Conclusion
According to IDC, there will be 44 zettabytes of data that may be structured or unstructured and can be generated from a variety of sources in 2020. This is the simple reason that fuels the demand for data analysts across the globe.
The best way to become a data analyst is to take up an online training course and get certified. The online training course ensures that you are prepared completely by giving you flexibility in learning at your own pace and also a choice in learning mode. In addition, there are doubt sessions carried out by industry experts to ensure that you are not lagging behind.
So, get yourself registered now!
