BigDataStack data services: an innovative big data toolbox

One of the major goals of the BigDataStack project is to build and give access to a set of data services to facilitate the ingestion of big data as well as its exploration through analytics.

Enterprise-scale Analytics Performance with Cloud Object Storage

Regardless the business you are involved in, the shared aim is one, to make your data less “big” or… to reduce the number of queries you run to process your data!

Call for Papers BigDataStack workshop at Closer2019

In conjunction with the 9th International Conference on Cloud Computing and Services Science, BigDataStack is organising its workshop "BigData Infrastructures".

BigDataStack Innovation Potential: Initial Plan and Activities

Enterprises today often have to use different database systems to fulfil different purposes, combining data coming from different data sources is not an easy task, while moving data from one source to the other is cost-demanding and requires ETLs and offline batch processing, which are often performed at night. Existing solutions today for polyglot applications often introduces the concept of datalakes or implements a federation on top of different sources in order to provide an easy way for common access. However, all these solutions are referring to different data sources, while for federation they are using technologies like Spark, which can be very resource consuming and cannot exploit the specific capabilities of each different data store.

BigDataStack at CLOSER2019

Big Data management is of outmost interest nowadays due to the large amount of data being generated every day in different domains ranging from user generated data to applications in banking, transport, e-commerce and heath care among others.

BigDataStack use cases: smart insurance

Insurance companies increasingly need IT data-based solutions in order to address their needs about the provision of services according to the customer “tailored” requirements. The challenge is to allow insurance companies to better develop the customer management, by providing personalized services to the customer, as well as new corporate services for the handling of the customers’ profitability. A multi-channel scenario will be developed by GFT which will facilitate data analytics-powered smart insurance, providing a 360-degree view of the customer and personalized services. GFT will collaborate with HDI Assicurazioni, part of the Talanx Group of Hannover, for its adoption.

IBM acquires RedHat, a game-changer for the cloud computing landscape with positive repercussions for Open Source in H2020 BigDataStack Project

IBM’s and Red Hat’s partnership has spanned 20 years, with IBM serving as an early supporter of Linux, collaborating with Red Hat to help develop and grow enterprise-grade Linux and more recently to bring enterprise Kubernetes and hybrid cloud solutions to customers. These innovations have become core technologies within IBM’s $19 billion hybrid cloud business. Between them, IBM and Red Hat have contributed more to the open source community than any other organization.

How to Layout Big Data in IBM Cloud Object Storage for Spark SQL

How to Layout Big Data in IBM Cloud Object Storage for Spark SQL

Are you familiar with storage systems like IBM Cloud Object Storage (COS) or Apache Spark SQL? Dr. Paula Ta-Shma from IBM, gives us some tips & tricks you should know to improve your daily data journey.

BigDataStack and the Data-Storage Challenge

One of the goals of BigDataStack is to facilitate scalable data storage through a distributed storage layer. This would enable storage across different resources, while supporting data migration for application components and re-allocation of data services across the infrastructure.

Bigdata Growth - A quick snapshot on its development

We are at an age where a single jet engine creates up to one terabyte (1,000,000,000,000) of data within a single transatlantic flight. Each one of us is like one of those engines, giving off ‘data exhaust’ as we operate in our daily lives. But these aren’t just inconsequential. In fact, big data is a worldwide market with more than estimated $203 billion worth of value by 2020.