Remove Data Architecture Remove Data Integration Remove Marketing Remove Structured Data
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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. The joint solution with Labelbox is targeted toward media companies and is expected to help firms derive more value out of unstructured data.

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Big Data Ingestion: Parameters, Challenges, and Best Practices

datapine

Large streams of data generated via myriad sources can be of various types. Here are some of them: Marketing data: This type of data includes data generated from market segmentation, prospect targeting, prospect contact lists, web traffic data, website log data, etc. Artificial Intelligence.

Big Data 100
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You Cannot Get to the Moon on a Bike!

Ontotext

Often, an enterprise starts with one thing it does well and then adds more business lines to expand the market. This requires new tools and new systems, which results in diverse and siloed data. And each of these gains requires data integration across business lines and divisions. We call this the Bad Data Tax.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

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Chose Both: Data Fabric and Data Lakehouse

Cloudera

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. Unified data fabric.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. For example, you can use C360 to segment and create marketing campaigns that are more likely to resonate with specific groups of customers. faster time to market, and 19.1%