IT PARK
    Most Popular

    Everything you need to know about artificial intelligence in the age of AI

    Jun 25, 2025

    Has the development of big data come to an end?

    May 19, 2025

    Ten application scenarios for blockchain

    Jun 29, 2025

    IT PARK IT PARK

    • Home
    • Encyclopedia

      What is a port?

      Jul 01, 2025

      What to do with a laptop blue screen

      Jun 30, 2025

      Is it better to save the file as a zip archive or as the original file?

      Jun 29, 2025

      What is cross-site scripting attack

      Jun 28, 2025

      The difference between SLR and digital cameras

      Jun 27, 2025
    • AI

      Can AI Painting Replace Human Painters

      Jul 01, 2025

      Who owns the copyright of the paintings created by AI for you?

      Jun 30, 2025

      How does the meta universe "feed" artificial intelligence models?

      Jun 29, 2025

      Amazon Bedrock: How to Stay Competitive in Generative AI

      Jun 28, 2025

      AGI Avengers! Google Brain and DeepMind officially announced a merger

      Jun 27, 2025
    • Big Data

      Transforming the construction industry through digital twin modeling

      Jul 01, 2025

      How does big data start? From small data to big data

      Jun 30, 2025

      What is big data? What can big data do?

      Jun 29, 2025

      Benefits of big data analysis and how to analyze big data

      Jun 28, 2025

      Six benefits of big data for enterprises

      Jun 27, 2025
    • CLO

      Essential factors to consider for a successful cloud transformation journey

      Jul 01, 2025

      Building a Smart City: The Importance of Cloud Storage

      Jun 30, 2025

      SaaS sprawl: meaning, hazard, status quo and mitigation plan

      Jun 29, 2025

      What are the advantages and disadvantages of hybrid cloud?

      Jun 28, 2025

      Cloud computing has many applications in our daily life, what are the main ones?

      Jun 27, 2025
    • IoT

      6 Ways the Internet of Things is Transforming Agriculture

      Jul 01, 2025

      4 Big Challenges for IoT Data Collection and Management

      Jun 30, 2025

      Most enterprises expect a return on investment within one year of IoT deployment

      Jun 29, 2025

      What are the main applications of IoT in our real life?

      Jun 28, 2025

      IoT systems and why they are so important

      Jun 27, 2025
    • Blockchain

      Blockchain Common Consensus Mechanisms

      Jul 01, 2025

      How energy company Powerledger (POWR) is using blockchain to improve the world

      Jun 30, 2025

      Ten application scenarios for blockchain

      Jun 29, 2025

      What is a privacy coin? What is the difference between them and Bitcoin?

      Jun 28, 2025

      The difference between Bitcoin cash and Bitcoin

      Jun 27, 2025
    IT PARK
    Home » Big Data » 10 Misunderstandings of Big Data Application
    Big Data

    10 Misunderstandings of Big Data Application

    The British science and technology news media V3 recently listed 10 relevant misconceptions about big data applications.
    Updated: Jun 19, 2025
    10 Misunderstandings of Big Data Application

    The British science and technology news media V3 recently listed 10 relevant misconceptions about big data applications.

    1. Big data is a new technology

    Big data is a new term, but its concept of massive data analysis is not new. Many people, including Stephen Brobst, chief technology officer of Teradata, believe that big data is misleading for users who are just beginning to realize the value of data. Brobst said: "Big data is a long-term project, not a 12-month period, but a 24-36 month period."

    1. Big data is a commodity

    When you first contact the concept of big data, you will think it is a special form of data, independent of other low-end data formats. But this is not the case.

    "Can you buy a database data?" said Donald Feinberg, an outstanding analyst at Gartner. "Yes, you can buy 100 servers, but can you buy big data? Therefore, this is not a market. It is only part of the IT market. It is worth 1 billion dollars? Yes, but it is not a market. It is not even a commodity, and it is not new."

    1. Big data is a problem

    This is an open argument with the nature of nearly half a dozen, but based on its basic form, big data has great potential, even if it is not used correctly or even not used at all.

    Therefore, as long as data exists and can be processed with an effective method in the future, there should be opportunities. It is also an expensive opportunity, maybe, but there is still an opportunity.

    The problem of data is how to transform it into clear and practical content through analysis, which is a huge challenge for enterprises.

    1. Your data is only useful to you

    According to Gartner, 30% of enterprises will find a way to cash in their data in the next few years. Selling user data to the highest bidder will cause fear and panic, but in nine cases out of ten it will be guaranteed or threatened.

    1. People don't care how you use their data

    Many people do not like targeted or relevant advertising, but it is a fact that big data driven marketing is the next focus. But when you enter a store and your mobile phone starts to vibrate, telling you that you can buy the same product at a lower price in a competitor's store, you will think of the service provider you signed.

    Even the harmless attempt to take advantage of people's behavior that has been criticized is of certain value. The WiFi Smartbin in London is a typical example. It keeps track of people's smart phone MAC addresses and displays targeted advertisements in the advertising bellows. Soon after the London City Management Company realized that this was happening, it banned this behavior, but it also reminded us of the $20 million class action lawsuit Facebook was facing.

    1. Big data won't land in prison

    At this point, we are dealing with a controversial topic. But Feinberg of Gartner is sure that there will be considerable data collection in this field.

    "How many CIOs will go to jail? If I think I'm joking, I'll make another bold assumption: I think the president of Facebook will go to jail before he leaves Facebook. I don't know when, but it will happen." Feinberg said, whether exaggerated or not, it is worth thinking about.

    1. The government is not interested in your social media data

    Many people like to abuse politicians on Twitter - they don't see it anyway, do they? Maybe, but it has certain reference value for understanding the intentions of voters, Feinberg said.

    "Obama cares because he was elected. If you look at how he was elected, his team uses social data and emotional analysis to find out who he can't win. I'm not saying that's the only reason why he was elected, but for government departments, social data and data have become very important." Feinberg said.

    1. You need new data for analysis

    After you have a business goal and the data warehouse is filled with 0 and 1, you can analyze and use your data. Research shows that most enterprises have started to use big data to obtain information. Once they think of a problem, they try to solve it through big data analysis.

    As DHL, the global logistics company, explained earlier to the reporter of V3, although there was tracking at every stage of parcel delivery, there was no way to use these data before the analysis system was established.

    1. Many people use big data

    Wrong. This is a worldwide problem.

    Gartner statistics show that there is such a shortage of skilled data analysis scientists that more than 75% of big data analysis positions are vacant in the company. The competition is fierce. In other words, it's a great career.

    That said, it also depends on how you define a data analysis scientist. Duncan Apthorp of Tesco, a big data analyst, said that his company does not require famous universities, which means ordinary graduates also have opportunities.

    1. Big companies know what they're doing

    Obviously not. According to Gartner's research on hundreds of enterprise cases: "In 2016, 85% of Fortune 500 enterprises will not be able to use big data to gain competitive advantage."

    Tasso Argyros, senior vice president of Teradata, said: Traditional business intelligence starts with a well-defined problem. For big data discovery, you have a starting point, but it is not a business problem, it is a business goal. The problem is that you don't know what questions to ask or what data to use, just say, 'Look at these data, let's start. It's usually easy to fail.

    Therefore, the answer to the question is "no". Not everyone knows what they are doing, and it is difficult to formulate strategies for efficient use of big data.

    big data big data application misunderstanding
    Previous Article Is Predictive Maintenance the Ultimate Solution for the Internet of Things
    Next Article Six big data mistakes that enterprises should avoid

    Related Articles

    Big Data

    How does big data start? From small data to big data

    Jun 30, 2025
    Big Data

    How Research Institutes Should Use Data Analytics Tools to Improve Research Efficiency

    May 18, 2025
    Big Data

    Talking about data lake and data warehouse

    Jun 05, 2025
    Most Popular

    Everything you need to know about artificial intelligence in the age of AI

    Jun 25, 2025

    Has the development of big data come to an end?

    May 19, 2025

    Ten application scenarios for blockchain

    Jun 29, 2025
    Copyright © 2025 itheroe.com. All rights reserved. User Agreement | Privacy Policy

    Type above and press Enter to search. Press Esc to cancel.