The data life cycle is no good to anyone as an abstract concept. Its purpose is to help deliver the data health that end-users need to fuel decisions.
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What product attributes make an offering more attractive to potential customers, and which features will make them stick around? What user-level insights can enable your marketing team to deploy more targeted customer campaigns? Which potential new product features should be prioritized to drive the most revenue? Product intelligence is the key to answering these and many other business-critical questions.
The architecture of a data lake refers to the features that are included within a data lake to make it easier to work with the data.
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Learn how data profiling can help organize and analyze your data produce new insights and give you competitive advantage in the marketplace.
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Data lakes and data warehouses are both widely used for storing big data, but they are not interchangeable terms. A data lake is a vast pool of raw data, the purpose for which is not yet defined. A data warehouse is a repository for structured, filtered data that has already been processed for a specific purpose.
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Data preparation is the process of cleaning and transforming raw data prior to processing and analysis. It is a time consuming process, but the business intelligence benefits demand it. And today, savvy self-service data preparation tools are making it easier and more efficient than ever.
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In this tutorial, generate random data and write them to HDFS. Then, read the data from HDFS, sort them and display the result in the Console.
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In this tutorial, create Hadoop Cluster metadata by importing the configuration from the Hadoop configuration files.
This tutorial uses Talend Data Fabric Studio version 6 and a Hadoop cluster: Cloudera CDH version 5.4.
1. Create a new Hadoop cluster metadata definition
Ensure that the Integration perspective is selected.
In the Project Repository, expand Metadata, right-click Hadoop Cluster, and click Create Hadoop Cluster to open the wizard.
In the Name field of the Hadoop Cluster Connection wizard, type MyHadoopCluster_files. In the Purpose field, type Cluster connection metadata, in the Description field, type Metadata to connect to a Cloudera CDH 5.4 cluster, and click Next.
Learn how to create Hadoop Cluster metadata automatically by connecting to the Cloudera Manager.
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In this tutorial, create a Big Data batch Job running on YARN, read data from HDFS, sort them and display them in the Console.
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Learn how to create a Big Data batch Job using the Spark framework, read data from HDFS, sort them and display them in the Console.
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Save time by using prebuilt Talend components to process and cache data, and access various sources such as NoSQL HBase, Hive, and RDMS tables in a Big Data Spark batch Job.
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This on-demand webinar presents the basics to get started with Talend’s Cloud API Services platform.
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Watch this on-demand webinar to learn how to create the right strategy for modernizing data warehousing and related data management by bringing them into the cloud
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Prescriptive analytics analyzes data and provides instant recommendations on how to optimize business practices to suit multiple predicted outcomes.
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The differences between structured and unstructured data can be summed up in data format, data storage, data type, data schema, and the data’s intended user.
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Big data analytics provides elevated shopping experiences, secure online payment, optimized pricing, and dynamic customer service to increase overall sales.
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Data centers collect hardware and ancillary devices to host networks, applications, and data. Cloud data centers are off-premises, managed by third-parties.
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See how 7 real-world companies — from healthcare to finance to retail — are putting modern BI solutions to work for their organizations.
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Watch Robin Davidson for a unique perspective on how DevOps can improve your efficiency as a developer and smooth out the operations process.
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Find out why privacy is an increasingly common concern across organizations that use big data to their advantage.
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BI and data mining work best when used in tandem, enabling businesses to make data-driven decisions that improve internal and external performance.
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Learn more about data silos, and how they can have a negative impact on your company.
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Find out why it’s no wonder many businesses are moving to cloud data warehouses.
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Learn about the differences between the two so you can identify which is best for your business.
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