“The temptation to form premature theories upon
insufficient data is the bane of our profession.”
Due to the ever-increasing growth of data collection, new ways to store, queue, and gain insights from digital information have been created in the past decade. Prohibitive costs involved in pushing individual supercomputers faster has led to a paradigm shift towards horizontal scaling (many computers working in parallel). Big Data Engineers create and manage these new tools, and are responsible for developing, maintaining, evaluating, and testing Big Data Solutions.
Why work with Data Insights?
The idea of Big Data entails uncountable new technologies, platforms, and methodologies. Every day new softwares, solutions, and approaches are developed and built upon. Via training and certification, Data Insights ensures that its consultants remain at the forefront of the domain. Working with us, you are guaranteed to be working with the current state-of-the-art.
Data Insights specialises in implementing Big Data Solutions, many of which have made up fascinating Use Cases over the years. Here we provide three quick examples:
Predictive Maintenance: Collections of machine-generated reports, as well as user behaviour tracking, can help to predict patterns in mechanical part failure. This can lead to optimised repair and logistical planning, which in turn lead to improvements in cost and environment
Fraud Detection: Tracking anomalies in customer profiles and behaviour, fraudulent transactions and users can be identified using the latest ML. technologies.
Sentiment Analysis: ML techniques now allow the extraction of a user’s sentiment, simply based on a small text blurb. This provides a powerful tool for enterprise to quickly summarize the feelings of the consumer base.
In all of these Use Cases, the role of Big Data Engineers is to build architecture allowing the collection and storage of required data: data pipelines, elaboration engines, streaming services, etc. Such architectures can be based upon a cluster of computers, be it a few dozen, or a few hundred.
“Big data is a field that treats ways to analyse, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.” The keywords here are ‘too large or complex’ and ‘traditional data-processing’. The total amount of data created, captured, copied, and consumed in the world is increasing rapidly in 2020 and it is forecasted to double for 2023. Due to the deluge of information we produce, ‘traditional data-processing’ is utterly inefficient in the analysis, filtering, understanding and value creation from all this data.