Cloudera

MAY 3, 2024

As a result, data scientists will often begin a project by developing an understanding of the data and the problem space and will then go out and find an example that is closest to what they are trying to accomplish. Like AMPs, Spaces are ML demo applications that are self-contained and instantly ready to deliver value upon deployment.

Project 52

Project Machine Learning Data Ingestion Professional Services 52

Data Engineering Podcast

JUNE 5, 2022

Summary The best way to make sure that you don’t leak sensitive data is to never have it in the first place. The team at Skyflow decided that the second best way is to build a storage system dedicated to securely managing your sensitive information and making it easy to integrate with your applications and data systems.

Data Security 100

Data Security Metadata MongoDB Scala 100

Ascend.io

DECEMBER 21, 2022

21, 2022 – Ascend.io , The Data Automation Cloud, today announced they have partnered with Snowflake , the Data Cloud company, to launch Free Ingest , a new feature that will reduce an enterprise’s data ingest cost and deliver data products up to 7x faster by ingesting data from all sources into the Snowflake Data Cloud quickly and easily.

Data Ingestion 52

Data Ingestion Google Cloud Data Lake Cloud 52

Rockset

APRIL 18, 2023

To highlight these new capabilities, we built a search demo using OpenAI to create embeddings for Amazon product descriptions and Rockset to generate relevant search results. In the demo, you’ll see how Rockset delivers search results in 15 milliseconds over thousands of documents. Why use vector search?

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

Monte Carlo

JUNE 14, 2022

I think we will look back at this conference as a major milestone for Snowflake, who today made claim to not just being the place organizations can store their data, but the place organizations build and monetize data applications. We’ve written previously about how building an external data product is hard.

Cloud 52

Cloud Data Ingestion Government Python 52

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Machine Learning 106

Machine Learning Python Kafka Java 106

Ascend.io

FEBRUARY 12, 2023

It turns out that instead of rapidly unlocking insights for the business, your data engineers are most likely bogged down in technical details, concerned about software code, QA, reliability, cloud security, and compute costs. Stakeholders have grown frustrated with how long it takes to build data pipelines.

Data Lake 52

Data Lake Business Analyst Data Pipeline Data 52

Ascend.io

FEBRUARY 12, 2023

It turns out that instead of rapidly unlocking insights for the business, your data engineers are most likely bogged down in technical details, concerned about software code, QA, reliability, cloud security, and compute costs. Stakeholders have grown frustrated with how long it takes to build data pipelines.

Data Lake 52

Data Lake Business Analyst Data Pipeline Data 52

Ascend.io

FEBRUARY 12, 2023

It turns out that instead of rapidly unlocking insights for the business, your data engineers are most likely bogged down in technical details, concerned about software code, QA, reliability, cloud security, and compute costs. Stakeholders have grown frustrated with how long it takes to build data pipelines.

Data Lake 52

Data Lake Business Analyst Data Pipeline Data 52

Monte Carlo

MAY 26, 2023

Fixing data freshness issues takes a long time : Because there are so many moving parts, troubleshooting data freshness incidents can take data engineers hours–even days. The root cause could be hidden in endless blocks of SQL code, a result of system permission issues, or just a simple data entry error.

Data Pipeline 98

Data Pipeline Data Data Warehouse Machine Learning 98

Rockset

DECEMBER 20, 2018

In this blog, I will show how Rockset can serve a live dashboard, which surfaces analytics on real-time Twitter data ingested into Rockset from a Kinesis stream. Setting up a Kinesis Stream The Python code snippet below shows how to create a Kinesis stream programmatically. import boto3 kinesis = boto3.client('kinesis')

AWS 52

AWS Kafka Data Ingestion Data 52

Confluent

MAY 22, 2019

We’ll also provide demo code so you can try it out for yourself. Since MQTT is designed for low-power and coin-cell-operated devices, it cannot handle the ingestion of massive datasets. On the other hand, Apache Kafka may deal with high-velocity data ingestion but not M2M. Demo of Scylla and Confluent integration.

Kafka 95

Kafka Google Cloud NoSQL Entertainment 95

Cloudera

APRIL 9, 2021

CML can leverage experiences in the earlier stages, such as data ingestion and data engineering, to fully automate data collection, cleansing and transformation before the prediction (ML) stage begins. . ML code can be easily developed and debugged within a CML workbench session. Schedule ML Jobs. Final Words.

Machine Learning 98

Machine Learning Manufacturing Data Collection Data Science 98

Snowflake

SEPTEMBER 11, 2023

Dynamic Tables support the same SQL join behavior, and we will illustrate this join behavior with the following sample code: 1. Set up the demo environment. Table 1: Information Mart Build as Dynamic Tables and Refresh Mode execution Can we achieve incremental refreshes when deploying a snapshot PIT table as Dynamic Table?

SQL 71

SQL Data Raw Data Architecture 71

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

Scala 64

Scala Data Lake BI Google Cloud 64

Rockset

JANUARY 16, 2019

Kafka is commonly used by many organizations to handle their real-time data streams. We will show how Rockset integrates with Kafka to ingest and index our fast-moving event data, enabling us to build operational apps and live dashboards on top of Rockset. The provided code includes a visualize.py Open the file.

Kafka 40

Kafka SQL Python Data 40

ProjectPro

JANUARY 19, 2022

ProjectPro has precisely that in this section, but before presenting it, we would like to answer a few common questions to strengthen your inclination towards data engineering further. What is Data Engineering? Data Engineering refers to creating practical designs for systems that can extract, keep, and inspect data at a large scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Cloudera

APRIL 15, 2019

While Cloudera Flow Management has been eagerly awaited by our Cloudera customers for use on their existing Cloudera platform clusters, Cloudera Edge Management has generated equal buzz across the industry for the possibilities that it brings to enterprises in their IoT initiatives around edge management and edge data collection.

Management 17

Management Data Ingestion Data Collection Government 17

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. The significant difference today is that companies use Apache Kafka as an event streaming platform for building mission-critical infrastructures and core operations platforms. Connecting Kafka to Rockset.

Kafka 20

Kafka BI SQL Datasets 20