Data Analytics In The Modern World

By: Haris Naeem

Do you find word puzzle games difficult? Well, it's all about deriving a list of words from a series of meaningless letters.

A very long time ago in ancient Greece, a temple was dedicated on Mount Parnassus to Apollos, their god of archery, music, truth, and healing.

Pythia, the priestess who lived in the sacred area of the temple would inhale the aromatic vapors expelled from a hole on the mountain.

As a result of that, she would exhibit wild behaviors and connect with the god. She would then go-ahead to speak "rubbish" which would later be analyzed and interpreted into prophecies by a priest.

The gibberish words or rubbish from the priestess can be referred to as RAW DATA. Same thing with a word puzzle game which usually seems confusing until you probably trace your name from it.

Companies all over the world collect large volumes of raw data which require appropriate analysis.

As rightly noted by Shafqat Islam, ''Behind each data point is a living, breathing human.''

The analysis of these gibberish raw data into well-defined forms is through a process called DATA ANALYTICS and the prophet in this case is a DATA ANALYST.

First of all, what is Data Analytics?
Data Analysis is the process of analyzing data to gain accurate insight and a deep understanding of the information they contain. It involves studying a data set to conclude the facts in them. Data Analytics is an overarching science or discipline that encompasses the complete management of data.

Digitalization has led to an increase in the volume of data in the world and yes, of course, it will continue to increase. A complex and large volume of data is called BIG DATA and getting a sense from them requires advanced data analytics procedures.

Here's why Data Analytics may be the next oil...

The total volume of data in the world right now is about 50 zettabytes (1 zettabyte=1 billion terabytes) of which 80-90% are unstructured.

However, organizations are beginning to see the impacts of data analytics. Studies show that by 2024, the use of data analytics in analyzing data will increase by 500%.

Also, about 35% of organizations will take part in the data online activity by 2022

What conclusion can be drawn from this? Sooner or later, the demand for data analysts will increase. Definitely!


The data collected during population census can be described as MEANINGLESS until they are interpreted and logical conclusions are derived from them.

These logical conclusions can help the government in the following ways:

1. Determination of standard of living.

2. Development planning processes.

3. Determination of a country's labor force.

4. Determination of taxation.

According to history, the US Census Bureau spent seven years analyzing and processing the data obtained from her 1880 census. With the development of computers and improvements in analytics practices, data analytics is easier and more efficient today.

For instance, during the 2020 census in the united states, requests were sent to the citizens to complete the headcount online.

Also, through the aid of data analytics, companies can now set new targets. They can also determine the areas they should improve their services, and they can predict market movements. As a result, they are satisfying their customers better than ever before.

Interestingly, it's now possible to use data analytics in policing and security by analyzing historical data to foresee places where insecurity would likely occur.

Lastly, google processes over 20 petabytes of data daily. Other search engines also process large amounts of data. Do you think this would be possible without the help of data analytics?

One more thing! Data Analytics was deployed during the London Olympics to ensure the smooth movement of over 18 million sports lovers because they had predicted and anticipated the number before the event.

Data analysts use these tools to execute analytical processes. The choice of data analytics tools depends on how skilled the analyst is and the business requirement of the company.

Some are free and on the contrary, others are not. Amazon and LinkedIn are among the companies that use Tableau. It allows you to visualize, analyze and understand data.

Other tools include KNIME, EXCEL, PYTHON, APACHE, GOOGLE ANALYTICS, SQL Server, QLINK, SAS, POWER BI, Sisense, Thoughtspot, R, Rapid Miners, Splunk, Grafana, Redash, Mode.

Some organizations have data analytics problems for several reasons.

First. Inaccessibility of data or poor data quality. This means not having access to the right data at the right time.

This occurs either as a result of failure in storage or collapse of the host. A simple way to minimize this is by organizing regular seminars about data literacy for workers.

Second. Based on findings, there was an astonishing 15000% increase in the search for data analytics in 2012 as compared with 2011.

You may have seen posts of organizations searching for data analysts on LinkedIn and other sites. Maybe they’d hired data analysts who failed them in the past or maybe they’re hiring for the first time. In any case, we can argue that there is a shortage of data analytics experts.

Finally, many data analysts usually have problem with analyzing data from multiple sources, especially when the sources are unrelated. Then again, high volumes of data collection can overwhelm these analysts.


The following are Data Analytics courses are a great place to start to be a Data Analyst wizard:

1. Microsoft Certified Solutions Expert: Data Management and Analytics by Microsoft.

2. Associate Certified Analytics Professional (aCAP)

3. Certified Analytics Professional (CAP)

4. Cloudera Certified Associate CCA Data Analyst

In your best interest, you can visit Udemy, Coursera and utilize LinkedIn Learning to acquire more knowledge before you attempt those certifications.

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