BENEFICIAL PARTS OF DATA ANALYTICS COURSE

A data analysis course in Malaysia would help you understand all of these parts.

One data analyst or scientist does the job of looking at the big picture, while the others look at the small picture of running daily operations. In the modern world, there are zettabytes of data floating and multiplying at amazing speeds. In 2017, around 2.7 zettabytes of data were accumulated worldwide and the projected increase is estimated to be close to 163 zettabytes in 2025.

A data analysis program teaches you how to collect data, separate it according to its value for your purpose, and then draw certain conclusions in an easy-to-understand way that a common layman could not understand otherwise. A data analyst is someone who looks at the set in the sense that he is trying to improve the existing structure of things or is looking for areas that can be explored to make more profit in a given area or highlight trends or models that emerge from careful use. Accumulated Data The techniques or processes involved in data analysis are, for the most part, automated that analyze raw data, making them useful to humans by helping them make their systems or businesses more efficient and structured.

As mentioned earlier, a data analysis course will teach you how to do all of these things and more. The field of data analysis is vast and is growing at a rapid rate with each passing day. There is a great demand for professionals in this field, as evidenced by the famous Cambridge Analytica case, where the results of the data analysis were sought by governments and private actors and all ready to spend large sums of money. money for information. And in addition to good training, each success depends on your skills and your effectiveness as a data analyst/scientist, and if you're good at it, the sky is the limit in package terms.

The data analysis can be divided into 4 parts:

1. Descriptive analysis: As the name suggests, this type of analysis generally tells you what happened during a particular time period, whether sales increased, or whether consumption decreased in a specific area at any given time.
2. Diagnostic analysis: this process aims to understand why something happens and if there is a cause and effect relationship between them. For example, some may try to understand the effect that a new marketing strategy could have on company sales, etc. And to that end, it could involve good deductions.
3. Predictive analysis: they try to make predictions about what can happen in the short term by analyzing data from the past where similar situations prevailed. For example, someone can try to predict what will happen to sales during a hot summer by studying the effects that a hot summer has had on sales in recent years.
4. Prescriptive analysis: These, on the other hand, focus on developing an action plan by collecting and examining available data. As if there is a high probability that there will be a hot summer, then how many tanks should be added in a brewery or how working hours should be adjusted so as not to lose productivity.

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Address: 360DigiTMG - data analytics, IR 4.0, AI, Machine Learning Training in Malaysia

Level 16, 1 Sentral,, Jalan Stesen Sentral 5,, KL Sentral,KL Sentral 50470 Kuala Lumpur, Malaysia

phone no: 011-3799 1378

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