• LEA 2019 - Leanne Tan Mar 29, 2020

    For Leanne Tan, success does not come alone. Teamwork makes the dreamwork!

    ๐Ÿ“ฃWant to be a part of LEA?
    ๐—–๐—น๐—ถ๐—ฐ๐—ธ:โ€ฆ/1FAIpQLSd4keczromi--Ahnโ€ฆ/viewformโ€ฆ ๐˜๐—ผ ๐—ป๐—ผ๐—บ๐—ถ๐—ป๐—ฎ๐˜๐—ฒ ๐—ป๐—ผ๐˜„!

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  • LEA 2019 - YM Tengku Datin Nuzaheran Tengku Hisham Mar 28, 2020

    YM Tengku Datin Nuzaheran Tengku Hisham shows that with dedication, grit, and a bit of patience, you can reach the pinnacle of success!

    ๐Ÿ“ฃWant to be a part of LEA?
    ๐—–๐—น๐—ถ๐—ฐ๐—ธ: ๐˜๐—ผ ๐—ป๐—ผ๐—บ๐—ถ๐—ป๐—ฎ๐˜๐—ฒ ๐—ป๐—ผ๐˜„!

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  • Have you ever wonder who your potential target market is? Mar 27, 2020

    Have you ever wonder who your potential target market is?

    Have you ever wonder who your potential target market is? What do they want and why do they buy your product? When do they make a purchase or even how to attract them?

    To answer those questions, one needs to have data analysed to understand the market. To collect the data and have it analysed is, however, not an easy task. We generate a massive amount of data on a global scale, which continues to increase at an unparalleled rate. The pace of data generation is also accelerated by other factors like the evolution of new technologies and models such as the Internet of Things (IoT).
    All these massive volumes of data are being created at high speeds from various sources like mobile devices, social media, and multiple sensors surrounding us. Nevertheless, with the advancement of technology in this era, we are able to accomplish that easily by using Big Data.

    ๐–๐ก๐š๐ญ ๐ข๐ฌ ๐๐ข๐  ๐ƒ๐š๐ญ๐š ๐š๐ง๐ ๐ก๐จ๐ฐ ๐๐จ๐ž๐ฌ ๐ข๐ญ ๐ก๐ž๐ฅ๐ฉ ๐ฎ๐ฌ?

    The definition of big data is unseen in the dimensions of data. For data sets to be defined as big data, a high degree of these three dimensions are needed; ๐—ฉ๐—ผ๐—น๐˜‚๐—บ๐—ฒ, ๐—ฉ๐—ฒ๐—น๐—ผ๐—ฐ๐—ถ๐˜๐˜†, and ๐—ฉ๐—ฎ๐—ฟ๐—ถ๐—ฒ๐˜๐˜†. As the era advances, two more dimensions are added to define big data, which are ๐—ฉ๐—ฎ๐—น๐˜‚๐—ฒ and ๐—ฉ๐—ฒ๐—ฟ๐—ฎ๐—ฐ๐—ถ๐˜๐˜†. The two are often proposed for business advantages.
    These five dimensions are commonly known as the following:
    โ€ข Velocity: the speed of data that are generated
    โ€ข Volume: the amount of data that are generated
    โ€ข Variety: the diversity or different types of data
    โ€ข Value: the worth of the data or the value it has
    โ€ข Veracity: the quality, accuracy, or trustworthiness of the data

    Vast volumes of data are generally reachable in either structured or unstructured formats. Machines or humans can create structured data, which has a detailed model and are frequently kept in databases. Structured data are prearranged around schemes with visibly defined data categories. Numbers, date, and time are some of the examples of structured data that may be kept in database columns. Alternatively, unstructured data does not have a predefined model. Text files, log files, social media posts, mobile data, and media are various types of examples of unstructured data.

    According to a research done by Gartner, an international research and consulting organization, the application of advanced big data analytics is part of the Gartner Top 10 Strategic Technology Trends for 2019 and is predicted to stimulate new business opportunities. The same report also forecasts that over 40% of data science tasks will be computerized by 2020, which will likely require new big data tools and paradigms.

    By 2017, global internet usage reached about 47% of the worldโ€™s population, according to an infographic provided by DOMO. This shows that a cumulative amount of people are using mobile phones with an increased number of devices being connected through smart cities, wearable devices, Internet of Things (IoT), and more. As internet usage grows and other technologies such as social media, IoT devices, and mobile phones continue to evolve, we will become more connected and generate extraordinary amounts of data, all of which will require new technologies for processing.

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