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  • Implementing Agile in Data Warehouse Projects

    This post talks about using an agile implementation for data warehouse projects.

  • Google unveils Mesa - Geo-Replicated Near-Realtime Scalable Data Warehouse

    Google has unveiled their new data-warehouse called Mesa. Mesa is a system that scales across multiple data centers and processes petabytes of data, while being able to respond to queries in sub-second time and maintain ACID properties.

  • Teradata Offers Data Warehouse as a Service as Part of Their Cloud Strategy

    Teradata revamps its cloud offering, offers Data Warehouse Data Platform as a Service solution. Teradata Cloud is aspiring to become a worthy competitor to Amazon Redshift, with a richer set of predefined libraries and a more effective way of loading data.

  • Amazon Makes Compelling Case for Hosting and Processing Your Big Data

    The AWS team has announced a limited preview of Amazon Redshift, a cloud-hosted data warehouse whose cost and capabilities are poised to disrupt the industry. In addition, AWS revealed two new massive compute instance types, and a data integration tool called Data Pipeline.

  • Better Developer Experience in Version 1.5 of the Data Access Framework MetaModel

    Eobject.org's open-source Java framework MetaModel implements a unified API for the access, exploration, and query of different datastores. Eobjects.org, both a website and an open source software organization dedicated to "the development of Open Source software related to Business Intelligence and Data Warehousing", has recently published version 1.5 of MetaModel.

  • Facebook on Hadoop, Hive, HBase, and A/B Testing

    The Hadoop Summit of 2010 included presentations from a number of large scale users of Hadoop and related technologies. Notably, Facebook presented a keynote and details information about their use of Hive for analytics. Mike Schroepfer, Facebook's VP of Engineering delivered a keynote describing the scale of their data processing with Hadoop.

  • Mahout 0.3: Open Source Machine Learning

    The need for machine-learning techniques like clustering, collaborative filtering, and categorization has steadily increased the last decade along with the number of solutions needing quick and efficient algorithms to transform vast amounts of raw data into relevant information. Apache Mount 0.3 has been announced on March, adding more functionality, stability and performance.

  • Event Stream Processing: Scalable Alternative to Data Warehouses?

    Dan Pritchett suggests that analyzing streams of events using Event Stream Processor could be an interesting alternative solution to data warehousing applications, which have, in his opinion, important downsides in terms of cost, scalability and reactivity.

  • Agile Business Intelligence

    Large centrally designed BI systems often don't meet the expectations of their end users. In this article at Cutter IT journal Scott Ambler has written about using Agile methods to help meet the user's expectations and deliver business value quickly.

  • Michael Stonebraker: Major RDBMSes are legacy technology

    Michael Stonebraker, co-founder of the Ingres and Postgres relational database management systems (RDBMS) and CTO of Vertica Systems, laid the framework for a debate in the database community by declaring that most major databases should be considered legacy technology.

  • ActiveWarehouse, a New Step for Enterprise Ruby

    ActiveWarehouse, is a significant new plugin that makes it easier to build data warehouses in Rails.

  • Practitioners Adapt Agile to Local Constraints

    Some people think they can only be Agile with small, co-located teams and full management support, but most teams aren't that lucky. So, should they should give up on Agile techniques? Scott Ambler's answer is a resounding "No!" His Dr. Dobbs article "Imperfectly Agile: You Too Can Be Agile!" outlines how Agilists overcome common challenges that others use as excuses for not being Agile.

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