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How Snowflake Enhanced GTM Efficiency with Data Sharing and Outreach Customer Engagement Data

Snowflake

However, that data must be ingested into our Snowflake instance before it can be used to measure engagement or help SDR managers coach their reps — and the existing ingestion process had some pain points when it came to data transformation and API calls.

BI 74
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Druid Deprecation and ClickHouse Adoption at Lyft

Lyft Engineering

In this particular blog post, we explain how Druid has been used at Lyft and what led us to adopt ClickHouse for our sub-second analytic system. Druid at Lyft Apache Druid is an in-memory, columnar, distributed, open-source data store designed for sub-second queries on real-time and historical data.

Kafka 104
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Using other CDP services with Cloudera Operational Database

Cloudera

In the previous blog post , we looked at some of the application development concepts for the Cloudera Operational Database (COD). In this blog post, we’ll see how you can use other CDP services with COD. Integrated across the Enterprise Data Lifecycle . Cloudera Data Engineering to ingest bulk data and data from mainframes.

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Tips to Build a Robust Data Lake Infrastructure

DareData

In this blog post, we aim to share practical insights and techniques based on our real-world experience in developing data lake infrastructures for our clients - let's start! The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

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How Rockset Enables SQL-Based Rollups for Streaming Data

Rockset

The latest Rockset release, SQL-based rollups, has made real-time analytics on streaming data a lot more affordable and accessible. Anyone who knows SQL, the lingua franca of analytics, can now rollup, transform, enrich and aggregate real-time data at massive scale.

SQL 52
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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. The second step for building etl pipelines is data transformation, which entails converting the raw data into the format required by the end-application.