hybrid data warehouse

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By: Attunity     Published Date: Jan 14, 2019
This whitepaper explores how to automate your data lake pipeline to address common challenges including how to prevent data lakes from devolving into useless data swamps and how to deliver analytics-ready data via automation. Read Increase Data Lake ROI with Streaming Data Pipelines to learn about: • Common data lake origins and challenges including integrating diverse data from multiple data source platforms, including lakes on premises and in the cloud. • Delivering real-time integration, with change data capture (CDC) technology that integrates live transactions with the data lake. • Rethinking the data lake with multi-stage methodology, continuous data ingestion and merging processes that assemble a historical data store. • Leveraging a scalable and autonomous streaming data pipeline to deliver analytics-ready data sets for better business insights. Read this Attunity whitepaper now to get ahead on your data lake strategy in 2019.
Tags : data lake, data pipeline, change data capture, data swamp, hybrid data integration, data ingestion, streaming data, real-time data, big data, hadoop, agile analytics, cloud data lake, cloud data warehouse, data lake ingestion, data ingestion
     Attunity
By: Teradata     Published Date: May 02, 2017
Constellation Research presents case studies of two companies that cut costs, gained flexibility, and eased administration by adding cloud data warehouse capacity to their on-premises environment. Both of these deployments: • Solved problems and yielded expected and unexpected benefits • Required some adjustments to administrative processes and expectations • Led to hybrid architecture as being an invaluable aspect of their respective data warehousing strategies Download the case studies now to explore each company’s journey, understand recurring themes, and walk away with actionable insights.
Tags : cloud data, online marketing, customer acquisition, mobile marketing, social marketing, data warehouse, data storage, data collection
     Teradata
By: IBM     Published Date: Nov 08, 2017
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
Tags : data warehouse, analytics, ibm, deployment models
     IBM
By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
Tags : data warehouse, analytics, hybrid data warehouse, development model
     Group M_IBM Q1'18
By: Group M_IBM Q119     Published Date: Mar 11, 2019
This report explores a new breed of data warehouse that can operate in a world of legacy on-premise systems while exploiting the potential of cutting edge technologies and deployment styles
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     Group M_IBM Q119
By: Group M_IBM Q2'19     Published Date: Apr 02, 2019
As the foundation for most critical business decisions, today's data environments are not just a vital piece of IT infrastructure, but key component of corporate strategy.
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     Group M_IBM Q2'19
By: StreamSets     Published Date: Sep 24, 2018
The advent of Apache Hadoop™ has led many organizations to replatform their existing architectures to reduce data management costs and find new ways to unlock the value of their data. One area that benefits from replatforming is the data warehouse. According to research firm Gartner, “starting in 2018, data warehouse managers will benefit from hybrid architectures that eliminate data silos by blending current best practices with ‘big data’ and other emerging technology types.” There’s undoubtedly a lot to ain by modernizing data warehouse architectures to leverage new technologies, however the replatforming process itself can be harder than it would at first appear. Hadoop projects are often taking longer than they need to create the promised benefits, and often times problems can be avoided if you know what to avoid from the onset.
Tags : replatforming, age, data, lake, apache, hadoop
     StreamSets
By: Oracle Corporation     Published Date: May 11, 2012
Exadata Hybrid Columnar Compression is an enabling technology for two new Oracle Exadata Storage Server features: Warehouse Compression and Archive Compression. We will discuss each of these features in detail later in this paper, but first let's explore Exadata Hybrid Columnar Compression - the next generation in compression technology.
Tags : oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands, enterprise applications, data management
     Oracle Corporation
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