Ascend.io

JUNE 6, 2023

In the world of cloud computing, efficiency isn’t just about running operations faster or smoother — it’s also about achieving more with less. Understanding and controlling cloud costs is a fundamental part of how Ascend manages the cloud infrastructure of our dedicated deployment customers.

Cloud 52

Cloud Data Pipeline Data Ingestion Cloud Storage 52

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 67

Data Warehouse Cloud Kafka Cloud Storage 67

Ascend.io

FEBRUARY 23, 2024

Before we explore the specific requirements your AI data platform, let’s evaluate your technical foundation’s readiness for AI. Critical considerations include: Do you have the cloud capabilities necessary to scale with AI’s demands? Is your data environment diverse and accessible enough to fuel AI algorithms?

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

Data Engineering Podcast

JUNE 12, 2022

Another category of unstructured data that every business deals with is PDFs, Word documents, workstation backups, and countless other types of information. In this episode Rod Christensen shares the story behind Aparavi and how you can use it to cut costs and gain value for the long tail of your unstructured data.

Unstructured Data 130

Unstructured Data MongoDB Scala MySQL 130

Knowledge Hut

AUGUST 18, 2023

With the rise of cloud computing, there’s no better time to explore the top Google Cloud Certifications that can take your career to new heights. Having gone through the process myself, I can attest to the immense value & recognition that comes with earning a Google Cloud Certification. What is Google Cloud Certification?

Google Cloud 52

Google Cloud Certification Cloud Cloud Computing 52

Towards Data Science

MARCH 5, 2024

In that case, queries are still processed using the BigQuery compute infrastructure but read data from GCS instead. Such external tables come with some disadvantages but in some cases it can be more cost efficient to have the data stored in GCS. Load data For data ingestion Google Cloud Storage is a pragmatic way to solve the task.

Bytes 74

Bytes Google Cloud Cloud Storage Utilities 74

RandomTrees

SEPTEMBER 6, 2020

Snowflake Overview A data warehouse is a critical part of any business organization. Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS).

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

DareData

JANUARY 30, 2023

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS).

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Monte Carlo

APRIL 24, 2023

With our new partnership and updated integration, Monte Carlo provides full, end-to-end coverage across data lake and lakehouse environments powered by Databricks. But remember that line from the introduction about the blurring line between data warehouses and data lakes? It works in both directions.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Towards Data Science

NOVEMBER 4, 2023

It simply makes sense to perform required data transformations, such as cleansing, enrichment and extraction in the place where data is being stored. Often it is a data warehouse solution (DWH) in the central part of our infrastructure. The downside of this approach is it’s pricing model though. ML model training using Airflow.

Data Engineering 88

Data Engineering Data Engineer Engineering BI 88

Rockset

MARCH 5, 2021

Understanding the space-time tradeoff in data analytics In computer science, a space-time tradeoff is a way of solving a problem or calculation in less time by using more storage space, or by solving a problem in very little space by spending a long time. However for each query it needs to scan your data.

Cloud Storage 52

Cloud Storage Data Ingestion Data Warehouse Computer Science 52

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure, also known as Azure, is a well-known cloud computing service offered by Microsoft. It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. What is Azure Synapse?

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

AltexSoft

MAY 12, 2023

Tools and platforms for unstructured data management Unstructured data collection Unstructured data collection presents unique challenges due to the information’s sheer volume, variety, and complexity. The process requires extracting data from diverse sources, typically via APIs. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Rockset

MARCH 1, 2023

Rockset introduces a new architecture that enables separate virtual instances to isolate streaming ingestion from queries and one application from another. Developers can spin up or down virtual instances based on the performance requirements of their streaming ingest or query workloads.

Architecture 59

Architecture AWS SQL Cloud Storage 59

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? It becomes especially important to have a data storage and processing layer when you start to deal with large amounts of data and are holding that data for a long period of time and need it to be readily available for analysis.

Building 52

Building BI Data Lake Data Governance 52

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

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. A dashboard that provides data in a graphical manner for in-depth study is the final product of this project.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

WeCloudData

OCTOBER 19, 2021

By leveraging data engineering techniques combined with a cloud toolchain, WeCloudData helped a client achieve a continuous flow of current job market data with analytical capabilities and dashboards to drive the business forward and stay competitive.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

By leveraging data engineering techniques combined with a cloud toolchain, WeCloudData helped a client achieve a continuous flow of current job market data with analytical capabilities and dashboards to drive the business forward and stay competitive.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

Knowledge Hut

APRIL 25, 2023

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Cloudera

FEBRUARY 16, 2022

Each workspace is associated with a collection of cloud resources. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 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.

Machine Learning 107

Machine Learning Python Kafka Java 107

Monte Carlo

OCTOBER 5, 2023

Aligning with stakeholders: SLAs, SLIs, and SLOs Many organizations adopt an approach to setting data quality standards that will be familiar to stakeholders: SLAs (service-level agreements), SLIs (service-level indicators), and SLOs (service-level objectives).

Government 52

Government Data Governance Data Datasets 52

Knowledge Hut

JULY 6, 2023

IT Professionals looking to work in the cloud domain are expected to have a sound understanding of Azure tools as well as development and monitoring tools. Azure Monitoring Tools: Overview Microsoft Azure is the second-most popular cloud service provider, next to Amazon Web Service. Why are Azure Tools Important?

Amazon Web Services 52

Amazon Web Services Data Lake Java SQL 52

Rockset

MARCH 21, 2019

When we started Rockset, we envisioned building a powerful cloud data management system that was really easy to use. Making the data stack simpler is fundamental to making data usable by developers and data scientists. Another key aspect of Rockset that makes it simple to use is its serverless nature.

SQL 52

SQL Data Management Management Engineering 52

Rockset

MARCH 15, 2021

While there’s typically some amount of data engineering required here, there are ways to minimize it. For example, instead of denormalizing the data, you could use a query engine that supports joins. This will avoid unnecessary processing during data ingestion and reduce the storage bloat due to redundant data.

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

AltexSoft

JULY 29, 2022

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. Today, companies have the opportunity to run Big Data analytics on Hadoop without investing in hardware.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

DECEMBER 7, 2021

Consequently, data engineers implement checkpoints so that no event is missed or processed twice. It not only consumes more memory but also slackens data transfer. Modern cloud-based data pipelines are agile and elastic to automatically scale compute and storage resources. ADF does not store any data on its own.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

MARCH 31, 2021

CDP Public Cloud is now available on Google Cloud. The addition of support for Google Cloud enables Cloudera to deliver on its promise to offer its enterprise data platform at a global scale. CDP Public Cloud is already available on Amazon Web Services and Microsoft Azure.

Google Cloud 89

Google Cloud Cloud Amazon Web Services Cloud Storage 89

Rockset

NOVEMBER 12, 2020

Elasticsearch is one tool to which reads can be offloaded, and, because both MongoDB and Elasticsearch are NoSQL in nature and offer similar document structure and data types, Elasticsearch can be a popular choice for this purpose. This blog post will examine the various tools that can be used to sync data between MongoDB and Elasticsearch.

MongoDB 40

MongoDB NoSQL Data Pipeline Data Storage 40

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. In Snowflake, there are three different storage layers available, Database, Stage, and Cloud Storage.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

ProjectPro

MAY 31, 2021

This project will teach you how to design and implement an event-based data integration pipeline on the Google Cloud Platform by processing data using DataFlow. Snowflake Real-Time Data Warehouse Project for Beginners Snowflake provides a cloud-based analytics and data storage service called "data warehouse-as-a-service."

Big Data 52

Big Data Coding Project Hadoop 52

Netflix Tech

DECEMBER 14, 2018

MDVS also serves as the storehouse and the manager for the data schema itself. As was noted in the previous post , data schema could itself evolve over time, but all the data, ingested hitherto, has to remain compliant with the latest schema. NMDB leverages a cloud storage service (e.g.,

Media 94

Media Database Metadata Data Schemas 94

Cloudera

OCTOBER 15, 2020

Data Discovery and Exploration (DDE) was recently released in tech preview in Cloudera Data Platform in public cloud. In this blog we will go through the process of indexing data from S3 into Solr in DDE with the help of NiFi in Data Flow. Spark as the ingest pipeline tool for Search (i.e. Index Data to DDE.

AWS 112

AWS Data Cloud Cloud Storage 112

Confluent

OCTOBER 16, 2019

Rapid analysis and visualisation of the real-time feed—in addition to historical data—is provided through Elasticsearch and Kibana. For more advanced analytics work, the data is written to two places: a traditional RDBMS (PostgreSQL) and a cloud object store (Amazon S3). SELECT * FROM TRAIN_CANCELLATIONS_00 ; Data sinks.

Kafka 19

Kafka Building Data Coding 19