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Data Vs Information. Learn Key Differences

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Did you know that Netflix – the biggest online streaming service that produces and releases top movies and TV shows (you know, Stranger Things & Squid Game) owes its success to Big Data? 

Their customer retention rate is 93%, the highest benchmark in the industry. 

Surely, you’ve glimpsed the term “Big Data” thrown in some bits of news, articles, or even podcasts that are relevant to data science. But what is it in a layman’s term? 

Well, first you need to understand that data is being produced every second you do anything on the internet, or even if you do nothing and just surf. This data gets accumulated at an unimaginable rate of zettabytes. 

The latest estimates state that 328.77 million terabytes of data are created each day. 

This chaos consists of extremely large, diverse, and complex collections of structured, unstructured, and semi-structured datasets that continue to grow exponentially. Big Data is chaos. 

Yes, Big Data refers to these huge and complex data sets that are challenging to analyze by traditional data-processing applications. 

Therefore, big organizations (such as Netflix, Amazon, etc.) collect them using processing applications with larger dataset capacities integrated with AI and ML to analyze, interpret, and mine data for valuable information and insights. 

Now that we’ve explored the expansive world of big data and its pivotal role in shaping industries like entertainment, it’s essential to understand a fundamental distinction: the difference between data and information.

Let’s delve deeper into today’s raging topic, Data vs information.

What is data?

We all remember what we have read since elementary school, the classic “Data is a collection of raw facts and figures”. Well, that hasn’t changed as it is the core of ‘Data’ but there is more to it than just that. 

Just as it is said in grounded theory methodology, “All is Data.

Grounded theory is a valuable tool for researchers in fields like sociology, where they collect data first, analyze it, and then let it guide them to further data that needs to be collected. 

With that data, they can refine the emerging theory rather than starting with a hypothesis and testing. 

This concept emphasizes that everything a researcher encounters during the study can be considered data, not just the traditional interview transcripts or observation notes. 

Even the field notes, interview recordings, participant artifacts, and even the researcher’s own observations and reactions, i.e. “all is data”

Likewise, data is not limited to individual facts or statistics, it can be anything from text, observations, symbols, images, codes, numbers, graphs, quantity, units, etc. 

It is divided into two major types which are quantitative and qualitative data

Value represented in numeric values such as the height & weight of a person, their age, income, expense, etc is quantitative data. 

Whereas, Value not represented numerically, rather it is textual and descriptive, such as the name of the person, their gender, hair, eye color, etc is qualitative data. 

Types of data for analysis

However, data generated on the web is not that simple. It is categorized into structured, semi-structured, and unstructured data. 

Structured data features elements that are formatted, organized, and readily available for effective analysis. They reside in a relational database, possess rational keys, and are easily mappable into pre-designed fields. For example: XLS file. 

Semi-structured data is partially organized, not in a formatted dataset or spreadsheet but it does have attributes that are easy to identify. It doesn’t exist in a relational database but it does have some organizational properties making it easier to analyze. For example: XML file. 

Unstructured data on the other hand has data that aren’t organized in any particular format. They exist in free forms like text documents, photos, speech transcripts, web pages, blog posts, social media posts, and customer feedback. 

It is scalable, flexible, and the most valuable asset for qualitative analysis. It is critical for sentiment analysis and allows you to gain the biggest competitive edge by uncovering trends and patterns in the market. For this, web data extraction is paramount. 

Information from these data types can be a treasure to one and random noise to another. But keep an eye out if you’re a business owner as it most definitely is a treasure to you, given that you know how to leverage it. 

Data to make or break your business
Get high-priority web data for your business, when you want it.

Data Vs Information 

Let’s look into how data and information differ from one another in different aspects.

“What is information then?” might be the next obvious question. 

Information is a meaningful result that helps in decision-making after we analyze the collected, and organized data. It has context, relevance, and purpose. 

It is the processed data used to take the next action. But, there is a catch to determining how authentic a piece of information actually is. We can compare it to accuracy, completeness, and timeliness. 

Before jumping to conclusions you should double-check and decide whether the data where the information is coming from is accurate, complete, and relevant as per the context.

Difference in Data Vs Information

DataInformation
Data is raw facts and figures that are yet to be processed and analyzed.  Information is processed and organized data with context, relevance, and purpose. 
Purpose: It serves as the foundation for generating information. Purpose: It serves in making business decisions, identifying problems/solutions, and gaining an understanding of a situation. 
Volume: It exists in large volumes generated continuously from the web. Volume: It is a condensed and synthesized form of the large volume of data into meaningful interpretations. 
Context: Raw data lacks context and usually doesn’t have immediate relevance. Context: Information on the other hand is contextualized and provides insights into the given situation or a problem.
Interpretation: It is stored with proper organization but to derive meaning, it requires interpretation and analysis. Interpretation: It is already processed and interpreted, available for consumption and decision-making. 
Significance: It is the most essential element (the raw material) that holds the potential to generate information to formulate business strategies. However, it does require processing and analysis to extract value. Significance: It is immediately useful and actionable for decision-making or problem-solving. It conveys valuable insights after data analysis to support decision-making. 
Example:
1. Number of traffic to a blog post in 3 months.
2. Average rating of a movie.
3. Price of a similar product on the competitor’s page.
Example:
1. Understanding what the people are searching for answers to. 
2. Identifying reasons why the movie is liked/disliked by the audience.
3. Determine if the competitor is selling the product at a higher or lower margin than the market rate. 

Journey from Data to information 

There exists quite a rigorous process of organization, analysis, and interpretation before data goes through metamorphosis to become information that is crucial for data-driven decision-making accelerating business growth. 

Let’s go through the process step-by-step. 

Collection of data

This is the beginning of extracting meaningful information. You can collect data from various sources on the web, surveys, social media, feedback forms, etc. For the easiest and hassle-free data extraction, reach out to Grepsr for fast, accurate, reliable, and real-time actionable data. 

Organization

Then, you must organize the mostly unstructured raw data you’ve collected into a clean format. So this process involves data sorting, categorizing, transforming, aggregating, and removing redundancies & error values for further analysis.

Pre-processing

You know its serendipity when you realize the service (Grepsr) that provides you quality data also does everything else mentioned above with its robust and rigorous probabilistic QA framework. 

That’s right, our QA process automatically detects any dataset abnormality like duplicate rows or missing values. Then, the seasoned team is right behind to fix those errors, they check and see whether each value in the data field matches the expected data type. 

We ensure the accuracy and reliability of the delivered datasets. Thus, the data you receive on your end is ready to be integrated into analytics tools. 

Processing and Analysis 

Now that the data is organized, it’s time for it to undergo processing and analysis. This phase consists of applying multiple analytical techniques like statistical analysis, predictive analysis, AI integration, data mining, machine learning, and more to extract insights, trends, and patterns in the database. 

Interpretation

As soon as you’re done with the analysis, you need to interpret it to derive meaning and relevant conclusions. This is when you can understand the insights in the context of the problem at hand. 

Contextualization

Okay, so you have the meaningful information, what’s next? When the information is placed in the right context, only then it proves to be significant for business decisions. It is vital to apprehend how the valuable insights fit within the larger picture of the organization. Also, how they can contribute to achieving the specific goals. 

Communication 

Finally, now is the time for data storytelling where the insights in the form of visual interpretations narrate a story of itself.

You can effectively convey the information that needs to be communicated to the stakeholders in your presentation by creating dashboards, charts, and graphs.

In this way, you can transform raw data into actionable insights with the help of data analytics, data storytelling, and visualization.

How can businesses make the most of data and information?

You might be questioning, why is the difference between data vs information significant for businesses anyway? 

Information gleaned from data can do wonders for your business if you know how to leverage it. 

Data alone cannot provide much value until transformed, processed, and analyzed for insights. Businesses tend to have limited time and resources for manual tracking of competitor’s activity to gain a competitive edge. 

But, with actionable information from data, they can properly monitor their competitor’s behavior and make informed decisions to position themselves better and outperform their rivals in the industry. 

Having said that, you must keep in mind that the quality of the data you have in the database has the biggest impact on the overall procedure. 

Manual extraction or the use of web-available tools compromises the primary characteristics of high-quality data, namely accuracy, reliability, completeness, relevance, and timeliness.

You can better opt for a real-time web scraping service like Grepsr that allows you to customize and specify your requirements while tailoring its solutions to fit your business needs. 

Unlock limitless possibilities for data-driven growth, innovation, and success with Grepsr by your side! 

Empower your team with unrivaled access to the most reliable, precise, and actionable web data available. 

Web data made accessible. At scale.
Tell us what you need. Let us ease your data sourcing pains!
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I’m sure you’ve already got the hang of Grepsr for Chrome by now. If you’re like some of our users who are inquiring about data delivery on the app, then this blog is for you! Once you’ve set up your project and the app starts to extract your data, depending on the volume of data requested, it might […]

Two Cool Features You May Have Missed in Grepsr for Chrome

If you’re in constant need of up-to-date and accurate data for your business, chances are you’re using our chrome extension, Grepsr for Chrome, to do the scraping. If you haven’t tried it yet, why haven’t you? It’s fun and easy to use! Although Grepsr for Chrome is already a powerful scraping tool, there might still be a few […]

web scraping with python

Track Changes in Your CSV Data Using Python and Pandas

So you’ve set up your online shop with your vendors’ data obtained via Grepsr’s extension, and you’re receiving their inventory listings as a CSV file regularly. Now you need to periodically monitor the data for changes on the vendors’ side — new additions, removals, price changes, etc. While your website automatically updates all this information when you […]

Kick-Start Your E-commerce Venture with Grepsr

400+ million entrepreneurs worldwide are attempting to start 300+ million companies, according to the Global Entrepreneurship Monitor. Approximately a hundred million new businesses start every year around the world, while a similar number also fold. What sets successful firms apart are the innovations and resources they utilize that help them stay healthy and relevant. Grepsr […]

How to Use Grepsr Browser Tool to Scrape the Web for Free

A beginner’s guide to your favorite DIY web scraping tool Just over a year ago, we introduced the all new Grepsr along with a beta launch of Chrome extension to fill the gap that Kimono Labs, a widely popular scraping tool, left since it’s closure. Now after a year of iteration on both the UI and UX along with shipping […]

Our Kimono Labs Replacement (Grepsr for Chrome) Levels Up

We’ve recently made a number of improvements to make Grepsr for Chrome that little bit easier, and more handy to use. We’ve also received tons of feature requests (keep ’em coming!), so we thought we’d share couple of our favorites that have most recently made it into Grepsr for Chrome. Infinite Scrolling and Enhanced Pagination Support From […]

Welcome To The (New) Grepsr Blog

Hello, Grepsr friends and family, and welcome to the next chapter of Grepsr Blog! It may not look much different yet, but we’re ramping up our editorial operation. Over the next few months you’ll see more posts, more announcements and analysis, more writing, and even new forms of content here. We’re still hammering out all the […]

Introducing the All New Grepsr

Chrome Extension, APIs, Better Support & Much More

Importance of Web Scraping in the Age of Big Data

Big Data has become an internet buzz lately. Not a day goes by without a mention of Big Data in many articles published by media or tech companies around the world.

FIVE Essential Questions for Assessing your Big Data Deployment Readiness

Big Data isn’t just a big buzzword. Nor is it merely a business ritual. Ask yourself these 5 essential questions to know if you business is ready for data-driven transformation in the Big Data era

Data Extraction for BI: Picking the Right Services is Crucial

Finding the appropriate data warehousing and Business Intelligence (BI) platforms that can understand and address your business concerns, priorities, and needs is a daunting task. Specifically, the ones that can have cohesive approaches in generating and deploying your data

Seven Key Areas Where Big Data has Brought Big Transformations

As the volume, variety, and velocity of Big Data increases, so does its value and application. Today, there is a widespread use of Big Data, and the whole fabric of life has become increasingly data driven. Here is a brief review of 7 major areas which have gone through massive transformations driven by data: Business Business enterprises […]

Data Mining for Developing Business Intelligence

The growing use of digital technologies in every sphere of life has resulted in the rapid escalation of digital data. While digitization of the facilities of everyday use has given rise to datafication, the process of datafication has produced a byproduct known as big data, which is regarded as a new oil of the digital […]

How Grepsr Works: A Brief Introduction

Web crawling and data extraction services at Grepsr are simple, quick, hassle free and intuitive. We focus on providing top–quality services to our customers in the highly competitive rates. Our strong base–with cutting-edge technologies and advanced infrastructure–in Kathmandu and our maturing technical expertise in the area have helped us to compete with the top tire […]

11 Interesting Quotes about Data

These days, almost everybody—be it a casual technophile or a trailblazing technocrat—has something to say about the usefulness of data. Apparently, there is no area of human interest where you cannot achieve agility, efficiency, and better outcome by deploying data science. Business, astronomy, neuroscience and you name it. Data had never been generated with such […]

Big Data & the Power of Personalization

According to Wikipedia, Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. “Doing business without advertising is like winking at a girl in the dark. You know what you are doing, but nobody else […]

Big Data is Redefining News & Journalism

If digital data were something physical, it would have massively altered the shape of our world, probably, with new data mountains rising every hour. Whether you browse the web or flip pages of print media, you are sure to stumble upon some news about big data, all the while feeding the web with your digital […]

Data Mining: How Can Businesses Capitalize on Big Data?

In the recent years, data mining has become a prickly issue. The big controversies and clamors it has gathered in the political and business arenas suggest its importance in our time. No wonder, it is used as a household name in the business world. Data mining, in fact, is an inevitable consequence of all the technological innovations […]

Leverage Grepsr to Turn Data into Asset

Have you ever been overwhelmed or even inundated by a sheer amount of data you have to handle every day? Handling too much of data can be a painstaking job in the age that has seen an enormous surge in digitization, quantification, and datafication of information. Today, you have to be equipped with data no […]

Welcoming New Year 2014 with Renewed Energy

2013 in the Retrospect 2013 was a very productive year for Grepsr. Measuring our success as a startup, we were able to maintain a steady progress in this year. We achieved a significant growth in terms of users, orders, and revenues, which was many times larger than 2012. During 2013, we managed to go global, […]

Web Scraping vs API

Every system you come across today has an API already developed for their customers or it is at least in their bucket list. While APIs are great if you really need to interact with the system but if you are only looking to extract data from the website, web scraping is a much better option. […]

Grepsr at Startup Asia event in Jakarta

We are just back from an awesome start-up event in Jakarta, Indonesia organized by TechInAsia. There were big investors and experts from the Asian tech industry at the event. We shared the stage with 15 other start-ups who pitched their product in front of a big crowd – it was an amazing experience! The reception […]

Web Crawling Software or Web Crawling Service

Some people ask us if we are a “service” or a “software”. We simply tell them – we are a service, with killer software that runs behind the scenes! 🙂 Also, lot of our customers ask us, why go for a Web Crawling Service over a Web Crawling Software? The answer is pretty straight forward. […]

Managed Data Extraction Service

Grepsr is what we like to call, “Managed Data Extraction Service”. Here are some of the reasons why we call it “managed”: We let you focus on your business and use the data — worrying about technical details of extraction is our job, and we will do it for you. We let you describe your […]

Official Launch of Grepsr (Beta)

We are immensely proud to launch Grepsr today. Grepsr is probably one of the first Web 2.0 Software as a Service (SaaS) products for website data extraction. So what does this mean for the customers? Cheaper costs – you pay a flat monthly fee no matter how big or small your extraction needs are. Fully […]

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