Tag: Hadoop

Feed: IBM Big Data & Analytics Hub - All Content; Author: kevin-wei; As coined by British mathematician Clive Humby, "data is the new oil." Like oil, data is valuable but it must be refined in order to provide value. Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes. Yet traditional ETL tools support only a limited number of delivery styles and involve a significant amount of hand-coding. In turn, enterprises are increasingly looking for machine-learning-powered integration tools to synchronize data for analytics, improve employee productivity, and prepare data for analytics.To achieve this, we ... Read More

Feed: Recent Announcements. Capacity Optimized allocation strategy uses real-time capacity data to allocate instances from the Spot Instance pools with the optimal capacity for the number of instances that are launching. This allocation strategy is appropriate for workloads that have a higher cost of interruption. Examples include long running jobs and multi-tenant persistent clusters running Apache Spark, Apache Hive and Presto.   The allocation strategy option also lets you specify up to five EC2 instance types per task node when creating your cluster with instance fleet configuration. This allows you to diversify your spot requests and hence get steep discounts ... Read More

Feed: Planet PostgreSQL. Overview It has been a while since I have written about the new features in a major pgpool II release. Well pgpool II 4.2 is in the works and the plan is to release it towards the end of this year. As usual every major release of pgpool II is compatible with the parser of latest PG release so pgpool II 4.2 will be compatible with PG-13 parser. There are many nice features that will be part of next major release however the ones that particularly catches my attention is supporting LDAP authentication with pgpool II. I ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: davendra-paltoo; A survey of end-users of Data Integration and Integrity (DII) software conducted by IDC in 2019 found that dynamic data movement, also known as data replication, is best served by stand-alone or platform tools, not custom code. When it comes to replication of data that is located in Virtual Storage Access Method (VSAM) environments, it’s likely that users would also prefer off the shelf software instead of custom code:Challenges of sharing data from VSAM environments Much mission critical data is managed, captured and stored in VSAM environments and ... Read More

Feed: IBM Big Data & Analytics Hub - All Content; Author: doug-dailey; A colleague recently shared a great quote with me from a mainframe CTO expounding on which platform is the “blue ribbon” winner for managing data across mainframe, IBM i, UNIX and Windows. “While everyone scurried around to figure out what platform won,a clear victor emerged: data” It makes sense; there is no single landing spot for data. Systems, servers and platforms have come into existence for decades with attempts to usurp the current technology of the day. Companies pursuing these latest technologies with an all-or-nothing approach have many ... Read More

Feed: Actian. Author: Pradeep Bhanot. In this second of a three-part blog series (part 1), we’ll explain how SQL execution in Actian Vector in Hadoop (VectorH) is much more functional and ready to run in an operational environment, and how the ability for VectorH to handle data updates efficiently can enable your production environment to stay current with the state of your business. In the first part of this three-part blog post, we showed the tremendous performance advantage VectorH has over other SQL on Hadoop alternatives. The third part will cover the advantages of the VectorH file format.Better SQL Functionality ... Read More

Feed: Teradata Blog. When it comes to enterprise analytics in the cloud, Teradata Vantage is incomparable–and when combined with the global footprint of Microsoft Azure, customers can use Vantage to achieve the highest levels of advanced analytics.Teradata Vantage on Azure enables users to scale as needed and integrate seamlessly with favorite business intelligence and visualization tools. Users can transform data into game-changing insights–whether in Vantage itself, Azure Blob, Azure Data Lake Storage, HDInsight, Hadoop, or other data stores.   Teradata is both a Gold Cloud Platform Partner as well as a Gold Analytics Partner within Microsoft. We’ve been working together to ... Read More

Feed: Actian. Author: Pradeep Bhanot. In this third and last part of the series on Actian Vector in Hadoop (VectorH), we will cover how the VectorH file format supports the performance and efficiency of our data analytics platform to accelerate business insights, as well as some of the other enterprise features that can help businesses move their Hadoop applications into production. Part one of this series showed the huge performance advantages VectorH has over other SQL on Hadoop alternatives, while part two explored the benefits of the richer implementation of SQL and the ability to perform data updates in VectorH.The ... Read More

Feed: Teradata Blog. When it comes to enterprise analytics in the cloud, Teradata Vantage is incomparable–and when combined with the global footprint of Amazon Web Services (AWS), customers can use Vantage to achieve the highest levels of advanced analytics. Teradata Vantage on AWS enables users to scale as needed and integrate seamlessly with favorite business intelligence and visualization tools. Users can transform data into game-changing insights–whether in Vantage itself, Amazon S3, Amazon EMR, Hadoop, or other data stores. Teradata is both an Advanced Technology Partner and an Advanced Consulting Partner within the AWS Partner Network (APN). We’ve been working together to optimize the ... Read More

Feed: R-bloggers. Author: n Posts on A stats websiten n. This post will be a quick introduction to using H2O through R. H2O is a platform for machine learning; it is distributed which means it can use all the cores in your computer offering parallelisation out of the box. You can also hook it up to already set up Hadoop or Spark clusters. It is also supposed to be industrial scale and able to cope with large amounts of data. You can install H2O from CRAN in the usual way using install.packages(). Once you load the package you can ... Read More