One of the most significant parts of any data-driven application is data quality assessment. Before you start using your data, you must understand how good - or bad - it is. This is why data analysis and data cleaning activities are performed - … Read more
Big Data Analyst
Big Data Analyst is specialized in collecting and processing big data to get useful information for the business and the various business units.
The skills required to a Big Data Analyst include knowledge in using database querying languages and big data analytics software, and a good understanding of data mining and extraction techniques, to provide companies with useful information.
This information can be used to analyze the market situation, the competitors and the customer's behavior, and is useful for marketing professionals and for those who are responsible for customer experience strategies.
Big Data Analysts are highly skilled in using data analysis software, a series of tools to store and analyze Big Data, so s/he's able to get and provide information to improve the activity of his company.
Find job offers in Job Search for Big Data Analyst.
Data is an essential part of data analytics, data security, and data science. That’s obvious. Sometimes, however, that data can get a little dirty. No, not like in a gangster film. More like where suddenly we are having to deal with ‘dirty data’ … Read more
With every second we spend online, mountains of data is generated. For every social media post, Google search, and link clicked, there is a way in which our activity can be collected for data. Experts within the data science field can utilize this, … Read more
So you’ve been out, you’ve conducted the surveys, you’ve collected a giant pot of data that unequivocally demonstrates your position and now it’s time to present. How do you do it? Well you could just dump the raw spreadsheet at the desk of your … Read more
Data analysts manipulate data and use it to help organisations make wise business decisions. They gather information from the data regarding specific aspects, interpret, analyse and share their findings with other stakeholders in the organisation … Read more
Table Of ContentsMainframe legacy languages persist beyond COBOLThe problem of expiring talentThe Linux Foundation's Open Mainframe Project is here to help Why learn a legacy mainframe language? The Common Business-Oriented Language (COBOL) is … Read more
Not all data scientists have a computer science background - I received my bachelor’s degree in Statistics, for example. As I moved into data, I noticed that I was good at scripting, but was not able to create a ‘production-quality’ code. A … Read more
A functional first-level framework to provide a service to users as an app. Let’s see the case for seismic data from both Italy-based and US-based open data collections. We are living in a highly vibrating world. The knowledge of many vibrations can … Read more
Humans are capable of walking on the moon. We can operate an International Space Station, and sending rovers onto the surface of Mars. We can launch hundreds of satellites into the unknown to gather data. We explore the universe, both personally and … Read more
Technologies behind databases have never been so variegated as today. After the rise of relational SQL-based databases, new needs have emerged, with the consequences of fostering a plethora of new database models, e.g. the NoSQL ones. Today, new … Read more
This article is an overview of GIS applied to the 3D field. GIS involves a lot of knowledge from different disciplines. As developers we have a lot of ways to use and combine these data sources. Sometimes I feel GIS is not so commonly known among … Read more
We often talk about cloud computing, artificial intelligence and machine learning, but just as frequently we forget all the software architecture that is behind these projects and how the data is treated, manipulated and managed. The databases are in … Read more
Starting to work in the processing of big data could be unsettling even for a developer who has solid foundations and experience in areas more related to "consumer" products. The software tools and computational systems for data science, in fact, … Read more
Imagine you are in the monitoring and control room of your city, where all relevant data coming from sensors, mobile devices, social media streams, IoT devices, vehicles and so on are displayed on multifunctional dashboards. Imagine you can read on … Read more
During the last decade, application development has extended its borders far and beyond the classical web application paradigm. In particular, two main tendencies arose, namely Cloud Computing and the Internet of Things. Delivering applications on … Read more
The SELECT for Cities project was conceived as a competition between companies operating in the Smart Cities sector and the Internet of Things (IoT), with the aim of identifying innovative solutions to specific problems in European cities. This is a … Read more
Integrated platforms and frameworks are the standard solution to the development, test and deployment of applications within complex environments: for example, no one today would program from scratch a neural network while there are plenty of … Read more
Interoperability is such a crucial term when your mind gets enlightened with your smartest idea. You start thinking how to make it work and the more advanced and complex your project, the more you start realising that problems should be tackled one … Read more
It is commonly understood that we are living in a “data era”: in the past we had the “commodity era”, when raw materials were the basis of economies and the only goods to be commercialized, next the “energy era”, when industrial productions emerged … Read more
As we know from the article on sentient cities, Snap4City is an open-source, standard-based, data-driven, service-oriented and user-centric platform, enabling large-scale co-creation of applications and IoT/IoE services. As the name suggests, it … Read more