Cloudera

MAY 3, 2024

The workflow—from data ingestion and model training to model deployment—is meticulously defined within a YAML configuration file. Like AMPs, Spaces are ML demo applications that are self-contained and instantly ready to deliver value upon deployment. Community AMPs The strength of Cloudera doesn’t end with its engineering staff.

Data Security 69

Data Security Machine Learning Data Ingestion Professional Services 69

Cloudera

MAY 3, 2024

The workflow—from data ingestion and model training to model deployment—is meticulously defined within a YAML configuration file. Like AMPs, Spaces are ML demo applications that are self-contained and instantly ready to deliver value upon deployment. Community AMPs The strength of Cloudera doesn’t end with its engineering staff.

Project 52

Project Machine Learning Data Ingestion Professional Services 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.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

The Modern Data Company

MAY 8, 2023

One of the most interesting features of a data lake is the “schema-on-read” principle, which means the data schema (the structure and organization of the data) is applied when the data is read or accessed rather than stored. See it in action and schedule a demo with one of our data experts today.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

One of the most interesting features of a data lake is the “schema-on-read” principle, which means the data schema (the structure and organization of the data) is applied when the data is read or accessed rather than stored. See it in action and schedule a demo with one of our data experts today.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

One of the most interesting features of a data lake is the “schema-on-read” principle, which means the data schema (the structure and organization of the data) is applied when the data is read or accessed rather than stored. See it in action and schedule a demo with one of our data experts today.

Data Management 52

Data Management Management Data Lake Data Governance 52

Monte Carlo

JUNE 14, 2022

Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Apache Spark, Trino, Flink, Presto, and Hive to safely work with the same tables, at the same time. Snowflake is going to be your unified platform for developing data applications from code to monetization. That story?

Cloud 52

Cloud Data Ingestion Python Government 52

Striim

OCTOBER 11, 2024

Data pipelines are significant to businesses because they: Consolidate Data: Data pipelines are responsible for integrating and unifying data from diverse sources and formats, making it consistent and usable for analytics and business intelligence. Schedule a demo for a personalized walkthrough to experience Striim.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Databand.ai

JUNE 28, 2023

Having a bigger and more specialized data team can help, but it can hurt if those team members don’t coordinate. More people accessing the data and running their own pipelines and their own transformations causes errors and impacts data stability. Want to learn more about how Databand can help you manage data pipelines?

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Cloudera

JANUARY 11, 2021

Over the last few weeks, I delivered four live NiFi demo sessions, showing how to use NiFi connectors and processors to connect to various systems, with 1000 attendees in different geographic regions. Interactive demo sessions and live Q&A are what we all need these days when working remotely from home is now a norm.

Kafka 62

Kafka Java Data Cleanse Datasets 62

Towards Data Science

JULY 8, 2024

I have used Colab for this demo, as it is much easier (and faster) to configure the environment. ML Pipeline operations begins with data ingestion and validation, followed by transformation. The transformed data is trained and deployed. . You can access it from here. Explore them here.

Data Preparation 46

Data Preparation Datasets Metadata Data Ingestion 46

Cloudera

APRIL 9, 2021

This integration is key in assuring that models evolve with the data – to avoid, for example, model drift. Thus, successful ML initiatives not only depend on the ability to quickly productionize models but they also depend on seamless access to data to train (and re-train) those models. Final Words. Additional Resources.

Machine Learning 98

Machine Learning Manufacturing Data Collection Data Science 98

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 98

Kafka Google Cloud NoSQL Entertainment 98

Ascend.io

OCTOBER 28, 2024

Tools like Python’s requests library or ETL/ELT tools can facilitate data enrichment by automating the retrieval and merging of external data. Read More: Discover how to build a data pipeline in 6 steps Data Integration Data integration involves combining data from different sources into a single, unified view.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. integration) and preprocessing need to run at scale.

Machine Learning 107

Machine Learning Python Kafka Java 107

Rockset

MARCH 1, 2023

Developers can spin up or down virtual instances based on the performance requirements of their streaming ingest or query workloads. In addition, Rockset provides fast data access through the use of more performant hot storage, while cloud storage is used for durability.

Architecture 59

Architecture AWS SQL Cloud Storage 59

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. You need to have a Twitter developer account in order to get access to the Twitter Streaming API. This can also be achieved through the AWS Console or the AWS CLI.

AWS 52

AWS Kafka Data Ingestion Data 52

Monte Carlo

MAY 26, 2023

Identify the business owners of those data assets. In other words, who will be most impacted by a data freshness or other data quality issue? Ask them how they use their data and how frequently they access it. Create a SLA that specifies how frequently and when the data asset will be refreshed.

Data Pipeline 98

Data Pipeline Data Data Warehouse Machine Learning 98

Ascend.io

FEBRUARY 12, 2023

Rather than becoming distracted by the complexity of data infrastructure, data product-driven companies have a much more impactful focus: the internal and external consumers of data and their goals. They want to hear how data is helping the business grow. They want to hear how data is helping the business grow.

Business Analyst 52

Business Analyst Data Lake Data Pipeline Data 52

Ascend.io

FEBRUARY 12, 2023

Rather than becoming distracted by the complexity of data infrastructure, data product-driven companies have a much more impactful focus: the internal and external consumers of data and their goals. They want to hear how data is helping the business grow. They want to hear how data is helping the business grow.

Business Analyst 52

Business Analyst Data Lake Data Pipeline Data 52

Ascend.io

FEBRUARY 12, 2023

Rather than becoming distracted by the complexity of data infrastructure, data product-driven companies have a much more impactful focus: the internal and external consumers of data and their goals. They want to hear how data is helping the business grow. They want to hear how data is helping the business grow.

Business Analyst 52

Business Analyst Data Lake Data Pipeline Data 52

Cloudera

MAY 28, 2019

CDSW gives data scientists the freedom to use their favorite open source and other vendor tools and libraries for the end-to-end ML workflow in addition to secure, self-service access to corporate data and distributed computing power, all managed efficiently and securely by IT. Stay tuned. Register today!

Data Science 50

Data Science Transportation Machine Learning Algorithm 50

Rockset

JUNE 21, 2022

Rockset, in contrast, is a real-time analytics platform that was built to serve sub-second queries on real-time data. Rockset efficiently organizes data in a Converged Index ™, which is optimized for real-time data ingestion and low-latency analytical queries. We invite you to start using the Snowflake connector today!

Kafka 52

Kafka Data Warehouse BI Analytics Application 52

Monte Carlo

APRIL 24, 2023

We continuously hear data professionals describe the advantage of the Snowflake platform as “it just works.” Snowpipe and other features makes Snowflake’s inclusion in this top data lake vendors list a no-brainer. The added structure and governance from Dataplex makes BigLake an intriguing data lakehouse option as well.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Cloudera

AUGUST 31, 2021

Due to the high storage cost in the legacy EDW solution, 100% source data capture proved cost-prohibitive – this led to continuing and costly change cycles to load incremental source updates as business requirements changed. Mainframe CDC using IBM Infosphere Data Replicator (IIDR). Ingested over 2,000 source system objects.

Data Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Cloudera

SEPTEMBER 6, 2018

Storage and processing can scale to petabytes, which eliminates the need to offload data to a slower storage medium. Having fast online access to years of AML data helps with investigations and data science activities. SDX helps to facilitate governance over enterprise data in order to satisfy regulatory inquiries.

Banking 40

Banking Machine Learning Big Data Scala 40

Monte Carlo

JULY 10, 2023

Accuracy reflects the degree to which the data correctly describes the “real-world” objects being described. For example, let’s say a streaming provider has 10 million overall subscribers who can access its content. According to the CRM’s data set, the streaming provider has 13 million subscribers.

Data Collection 40

Data Collection Data Governance Government Data 40

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. Because Rockset continuously syncs data from Kafka, new tweets can show up in the real-time dashboard in a matter of seconds, giving users an up-to-date view of what’s going on in Twitter.

Kafka 21

Kafka SQL BI Hadoop 21

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