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Data logs: The latest evolution in Meta’s access tools

Engineering at Meta

Here we explore initial system designs we considered, an overview of the current architecture, and some important principles Meta takes into account in making data accessible and easy to understand. Users have a variety of tools they can use to manage and access their information on Meta platforms. What are data logs?

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Use Data Enrichment to Supercharge AI

Precisely

Imagine accessing more detail based on each customer’s home address. You need reference data sets from trusted, authoritative sources like Precisely to do that. The post Use Data Enrichment to Supercharge AI appeared first on Precisely.

Raw Data 121
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Fueling Data-Driven Decision-Making with Data Validation and Enrichment Processes

Precisely

What times of the day are busy in the area, and are roads accessible? Data enrichment helps provide a 360 o view which informs better decisions around insuring, purchasing, financing, customer targeting, and more. Together, data validation and enrichment form a powerful combination that delivers even bigger results for your business.

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Data News — Week 23.16

Christophe Blefari

We will have 3 speakers and for the first time all the presentations we will held in English. Access — you will be able to namespace models with groups and visibility. We announced this week the May Paris Apache Airflow meetup. It will take place in Algolia offices, the 9th of May. In dbt Core 1.5

Raw Data 130
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Future Proof Your Career With Data Skills

Knowledge Hut

It looks like this: Data collection This part deals with the collection of raw data from various resources. All this data needs to be collected and stored in a place which is easy to access while working with the data. Data cleaning This is considered as one of the most important steps in data science.

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Take Digital Marketing to the Next Level with Enriched Demographic Data

Precisely

Digital marketing is ideally suited for precise targeting and rapid feedback, provided that business users have access to the detailed demographic and geospatial data they need. Read For Trustworthy Results, Build Data Integrity If you don’t have the right data, you can’t achieve excellent results.

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Fraud Detection using Deep Learning

Cloudera

It’s not the raw transaction data but rather an anonymized feature set based on a principle component analysis (PCA) of the original data. The data and the techniques presented in this prototype are still applicable as creating a PCA feature store is often part of the machine learning process. .