Analytics

integrate

BI Compliance: Can a Restructure Deliver Enhanced Data Privacy?

Jun 3, 2021 By Donal Tobin In Integrate
Every data-driven business is terrified of the prospect of a data breach. Exposing sensitive data could mean reputational damage, loss of clients, and heavy fines under emerging privacy laws. But every data-driven business also wants to make use of its data. Business intelligence (BI) platforms allow anyone to build complex and detailed dashboards that help them understand the organization’s current state. How do you resolve this tension? One approach is to build a privacy-first data structure.
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integrate

ELT: Easy to Deploy, Easy to Outgrow

Jun 3, 2021 By Abe Dearmer In Integrate
Extract, load, transform (ELT) technology is a type of data pipeline that ingests data from one or more sources, loads the data into its destination (typically a data lake), and then allows end-users to perform ad-hoc transformations on it as needed. ELT can perform mass extraction of all data types, including raw data, without the need to set up transformation rules and filters before data loading.
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Worksheet Best Practices - ThoughtSpot Success Series #5

Jun 3, 2021 By ThoughtSpot In ThoughtSpot
Introducing the ThoughtSpot Success Series! Want to expand your knowledge of ThoughtSpot? Want to learn some great tips and tricks? Join ThoughtSpot's Customer Success team and other users like yourself as we discuss various topics in our new Success Series. During this event, we'll share how to build a ThoughtSpot use case pipeline that allows you to maximize the value return on investment & maintain momentum.
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cloudera

Validations - Cloudera Support's Predictive Alerting Program

Jun 3, 2021 By Alexander Lavoie In Cloudera

Cloudera Support’s cluster validations proactively identify known problem signatures contained in customers’ diagnostic data with the goal of increasing cluster health, performance, and overall stability. Cluster validations are included in a customer’s enterprise subscription at no additional cost. All customers with access to the Support case portal will also be able to take advantage of cluster validations.

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integrate

What Does Customer 360 Mean?

Jun 2, 2021 By Abe Dearmer In Integrate
Collecting and analyzing data on your customers’ preferences and behavior is one of the best ways to improve your products and customer service. As your business grows, you need enterprise-class customer relationship management (CRM) software that can store and manage all of your customer data. Salesforce is a software as a service (SaaS) company that provides the Salesforce CRM software to more than 100,000 organizations worldwide.
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integrate

PII Substitution May Be the Future of Data Privacy

Jun 2, 2021 By Mark Smallcombe In Integrate
Unfortunately, most of us have had our sensitive data or personal information compromised at one point or another. Whether the leaked data involves credit cards, a bank account number, a social security number, or an email address, nearly everyone has been a victim of a third-party data breach. In 2020, over 155 million people in the U.S. — nearly half the country's population — experienced unauthorized data exposure.
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Realtime data replication into BigQuery with Datastream and Dataflow

Jun 2, 2021 By Google BigQuery In Google BigQuery
How can you replicate data from a relational database in real time? In this video, we’ll show you you can combine Datastream with Dataflow templates to replicate data from a relational database. Watch to learn how you can use this streaming analytics service in unison with Datastream to easily replicate data from Oracle to BigQuery in real time!
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Fast Forward Live: Session-based Recommender Systems

Jun 2, 2021 By Cloudera In Cloudera
Join us live with Fast Forward Labs to discuss the recently possible in Machine Learning and AI. Being able to recommend an item of interest to a user (based on their past preferences) is a highly relevant problem in practice. A key trend over the past few years has been session-based recommendation algorithms that provide recommendations solely based on a user’s interactions in an ongoing session, and which do not require the existence of user profiles or their entire historical preferences. This report explores a simple, yet powerful, NLP-based approach (word2vec) to recommend a next item to a user. While NLP-based approaches are generally employed for linguistic tasks, here we exploit them to learn the structure induced by a user’s behavior or an item’s nature.
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