Data Analytics, better known as Big Data, is the approach that allows companies to analyse big amounts of data generated in their activity enabling to draw conclusions that affect their business. A proper use of this data may even help them to improve their business turnover. Thus, improve operational efficiency, customer user experience and allows them to improve their business models.
All data generated by companies in their activity is one of the concerns they are facing today, including manufacturing sectors. They must evaluate the relevance of this information, which of it they need to store or even which part of all these data can be monetized.
Data analysis means the translation of information into opportunities for companies to take advantage of all data generated (Schneider,B. 2017). Therefore, “Data Analytics” is also called as a translator or business generator as it allows to explore personalised solutions to carry out more customized projects.
Nowadays, information as a service is a business model that is expanding wherein increasingly more businesses are seeking to monetise the information they get.
Number of services offered by platforms related to data analytics in industrial sectors keeps growing as well as new solutions in terms of storage capacities as well and processing capacity.
Some of the platforms that currently exist are as follows:
- Hadoop: http://hadoop.apache.org/
- Gridgain: https://www.gridgain.com/
- HPCC: https://hpccsystems.com/
- Storm: http://storm.apache.org/
- Spark: https://spark.apache.org/
- Hive: https://hive.apache.org/
- Kafka: https://kafka.apache.org/
- Flume: https://flume.apache.org/
Interested in learning more about Big data? A key milestone of the DTAM project is the training curriculum that will focus on five key areas, one of which will be Big Data. Follow us and stay tuned to learn when the training course will be available.
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