If you are aware of the latest technology terms, you must have heard about Data Analytics and Data Analysis. Since these terms appear similar, there is little or no scope for noticing their differences. More often, people think they are the same. Nevertheless, they are two individual terms with some differences. But what are they, and how does that matter? Let's find out in this article.
Let's break the common misconception that Data Analytics and Data Analysis are similar. No! they are not. Although they are co-related, they have significant differences between them. Let's take an example to comprehend this better. You all must be knowing about Idli, a very famous South Indian dish. This is everyday breakfast in most South-Indian households. So, this Idli is served with a side dish called chutney. You can enjoy your Idli either with onion chutney or coconut chutney (as per your preference!).
Both are chutneys, which does not imply that they taste the same. Moreover, without Idli, chutneys are of no worth.
Long story short, although Data Analytics and Data Analysis are individually significant, they are of no worth without the core component (main dish), i.e. Data.
Data Analytics vs Data Analysis
To begin with, "Analysis" is the process of examining something in-depth to determine its elements or structure. Alternatively, "Analytics" involves analyzing data through systematic computations. It implies that Data Analytics is a broad area that handles data employing various tools to make crucial decisions with useful predictions for a better outcome. On the other side, Data Analysis is a subtype of Data Analytics, and it aims to help us understand the data. It gathers valuable insights from the Data that is available.
In other words, Data Analytics is the process of examining data from the past to make better decisions in the future by availing of valuable insights. At the same time, Data Analysis helps us understand the data and offers valuable insights from the past to help us know what has happened so far.
Why does the discussion around these terms matter?
Both the terms Data Analytics and Data Analysis revolve around the information called the Data. Today, Data is not just a set of information. It has got so much more significance than ever before. It is counted as one of the most valuable assets in the modern business world.
You can probably rule the world if you know how to handle the data. Even the topmost tech giants like Google, Amazon, and Microsoft collect vast datasets and analyze them to maximize their outcomes. The data collected helps such companies analyze and understand customer preferences and mindsets.
In this context, the process of analyzing data becomes of prime significance. That's how the discussion around Data Analytics and Data Analysis has gained traction today.
What Are The Process And Tools Involved In Data Analytics And Data Analysis?
Following are the processes involved in Data Analytics:
- Identifying the issue
- Exploring the Data
- Data Filtering
- Data Authentication
- Data Cleaning
- Data Visualization
- Data Analysis
- Extrapolation
- Prediction
The most common tools used in Data Analytics are:
- Python
- SPARK
- SAS
- Excel
- Google Analytics
The process of Data Analysis comprises of the following:
- Data collection
- Data validation
- Interpretation
- Analysis
The most common tools used in Data Analysis are:
- Tableau
- SPARK
- Excel
- Node XL
- Google Fusion tables
Analytics can be employed in several ways like computing different correlations, finding the preferences, speculating market trends, understanding customer preferences etc.
On the other hand, analysis performs various processes as Predictive Analysis, Exploratory Data Analysis, and Inferential Analysis to explore different valuable insights.
Understanding Difference Between Data Analytics And Data Analysis With An Example
Data Analysis is simpler than Data Analytics. Let's take an example to comprehend this better:
Let's say you want to start trading in the share market. However, you are a beginner who knows a few basics of the same.
In this case, firstly, you will try to examine the previous trends in the share market. Thereby, you will get to know what has happened so far. Using that knowledge, you will frame the strategies that will help you earn more profits. This process corresponds to Data Analysis.
After you understand the trends, you will now employ various techniques to forecast the upcoming price trend of the shares. Based on this information, you will buy some shares. This process corresponds to Data Analytics.
Conclusion
This article has shared insights on the trending tech terms viz Data Analytics and Data Analysis. Read through the article to understand the basic difference between these two. Use this information to boost your knowledge regarding these crucial terms. Thereby, enhance your tech desire.
