Written by Alexander Raginsky In the near future, the following major trends are expected in Big Data analysis: Big Data technology will be based on a mixture of cloud and on-premises computing. Many corporations start migrating from in-house database infrastructures to cloud-based data warehouses. Distributed frameworks for data analytics like MapReduce are turning into distributed managers of resources and
Written by Alexander Raginsky Over the past few years, there have been talks about data management and administration of databases. It is indeed important for data to be managed properly for the best results. Businesses get to enjoy lots of benefits if they manage their data properly because data is an asset, and a very important one for that
Written by Alexander Raginsky Amazon.com is boosting its artificial-intelligence chops. The world’s largest retailer by market capitalization is rolling out its sophisticated big-data-crunching platform for developers in Europe, and is also hiring scientists for its research teams in New York and Berlin who specialize in getting machines to do things like make sales predictions and predict fraud. Machine learning
Written by Alexander Raginsky Enterprise software company Workday is launching a venture fund aimed at early to growth stage startups that are leveraging machine learning and data science to solve enterprise-level problems. In conjunction with this announcement, Workday is also naming the first four startups it has invested in. Run by Adeyemi “Ade” Ajao, the company’s vice president for
Written by Alexander Raginsky Machine learning deals with hundreds of algorithms that have various modifications. When selecting an appropriate class of algorithms and an algorithm within the class, you should closely consider your problem, define what you should measure or predict and which tools you are going to use for this purpose. A possible set of the best machine-learning
Written by Alexander Raginsky Big data is now a buzzword. Many developers work hard to improve the processing of large amounts of data and many data scientists work on data analysis problems. Nevertheless not all is well in this field. Big data cause big problems: Insufficient data integration. Data are stored in large warehouses and different groups of specialists
Written by Maxim 
Big Data and cross-language processing can be a very happy marriage that will open way to the new generation of powerful multilingual product. However, what is missing to let it happen already? What is the profile of the individual who will bring the multlingual Big Data to life? Read about it below. Big Data is a
Written by Alexander Raginsky CareerBuilder announced today that it has acquired a majority stake in Textkernel, a leading-edge software company providing semantic recruitment technology to the global market. The acquisition further supports CareerBuilder’s evolution into an HR software as a service provider and enables Textkernel to accelerate its global growth.Based in Amsterdam, Textkernel is leading innovation in the field
Written by Alexander Raginsky From 2nd to 5th of September 2015, the TU Dortmund University and LIAAD-INESC TEC will organize a Summer School on Data Sciences for Big Data – Resource Aware Data Mining. The School will be hosted at Faculty of Sciences, University of Porto and is collocated with ECMLPKDD 2015 – European Conference on Machine Learning and
Written by Alexander Raginsky Technology revolutions come in measured, sometimes foot-dragging steps. The lab science and marketing enthusiasm tend to underestimate the bottlenecks to progress that must be overcome with hard work and practical engineering. The field known as “big data” offers a contemporary case study. The catchphrase stands for the modern abundance of digital data from many sources
