The term data analytics is an evolving one that attempts to describe the huge amount of structured, unstructured and semi structured data which has the potential to provide useful information when mined. This data is used for machine learning training, projects and similarly advanced analytics apps.

certification on data analytics is usually determined with the help of 3Vs: various variety in data types, large volume of data, and the velocity required to process this data. Doug Laney, a Gartner analyst, was the first to identify these characteristics about data analytics in a report that was published in 2001. Other Vs have been added to the list like value, veracity and variability. While data analytics does not consist of data that is a specific size, the term is used to refer to volumes of data that can be measured in terabytes or sometimes exabytes.

The different Vs of data analytics

Huge amounts of data can be amassed from various kinds of sources like customer databases, business transactions, mobile apps, internet clickstream logs, medical records, social networks, results of experiments, real time data sensors utilized in different Internet of Things (IoT) and machine generated data. With the help of data mining tools, data preparation software can be used to analyze data that is left in its raw form.

data analytics certification also takes into consideration the different data types, even the structured data within the SQL databases and warehouses and unstructured data like document files and text that are held in Hadoop clusters. It also encompasses NoSQL systems, and also semi-structured data available from streaming data received from sensors and web server logs. It further includes simultaneous and multiple data sources that could not be integrated otherwise. A data analytics project, for example, can try to analyze and estimate a product’s success and the future sales of that product with the help of previous sales data, return data and also reviews received from online buyers for that product.

Velocity takes into consideration the speed at which course for data analytics is being generated as well as what speed it needs to be processed and analyzed. In most situations, a lot of data analytics is constantly updated in real time or almost real time when compared to daily, weekly and/ or monthly updates within many warehouses that are traditional. Projects that deal with data analytics analysis absorb, find correlations with and later analyze the data that is coming in. They then render it to provide a result or an answer that is based on an overarching query. Data analysts are hence required to have a very detailed understanding of the data they have available. They may often be required to possess a good sense of the answers and results that they may be searching for in order to be certain that the information that they have found is current and valid.

Become a data analyst and develop the knowledge required to decide what process is best to handle the data that your company is collecting. Get trained to handle data analytics better with data analytics training in.

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