Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Podcast

DECEMBER 21, 2021

Summary One of the perennial challenges of data analytics is having a consistent set of definitions, along with a flexible and performant API endpoint for querying them. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

Data Analytics 130

Data Analytics BI Computer Science SQL 130

Knowledge Hut

MARCH 7, 2024

Introduction to Big Data Analytics Tools Big data analytics tools refer to a set of techniques and technologies used to collect, process, and analyze large data sets to uncover patterns, trends, and insights. Importance of Big Data Analytics Tools Using Big Data Analytics has a lot of benefits.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

Netflix Tech

OCTOBER 27, 2020

By Tianlong Chen and Ioannis Papapanagiotou Netflix has more than 195 million subscribers that generate petabytes of data everyday. Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy.

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Data Warehouse Datasets Data Big Data 97

Propel Data

OCTOBER 11, 2022

The main difference between data lakes and data warehouses is data lakes allow unstructured data, but data warehouses need structured data.

Data Lake 40

Data Lake Data Warehouse Unstructured Data Data Analytics 40

Propel Data

AUGUST 1, 2022

Snowflake data platform is referred to as a data warehouse or data lake because it separates storage (data) from compute (processing power).

Data Warehouse 40

Data Warehouse Data Analytics Data Lake Data 40

Edureka

JUNE 1, 2023

This is where AWS Data Analytics comes into action, providing businesses with a robust, cloud-based data platform to manage, integrate, and analyze their data. In this blog, we’ll explore the world of Cloud Data Analytics and a real-life application of AWS Data Analytics.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Propel Data

AUGUST 24, 2022

With Snowflake, it’s possible to build an enterprise data warehouse (EDW), an operational data store (ODS), or a team-specific data mart.

Data Warehouse 40

Data Warehouse Data Analytics Data Building 40

Knowledge Hut

OCTOBER 6, 2023

Recently, the AWS Data Analytics Certification has captured my attention, and I have been researching the many AWS data analytics certification benefits. I'll delve into the specifics in this post to help you determine if AWS Data Analytics certification is worth it. What is AWS Data Analytics?

AWS 52

AWS Certification Data Analytics IT 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

JANUARY 12, 2024

We’ve previously discussed the need for quality over quantity when it comes to big data and, in this article, we’ll be looking at how recent technological innovations and new processes across 4 of the 5 ‘V’s of big data (volume, velocity, veracity, variety) are changing the future of big data analytics.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

Cloudera

DECEMBER 20, 2022

Try Cloudera DataFlow (CDF), Cloudera Data Warehouse (CDW), Cloudera Data Engineering (CDE), and Cloudera Machine Learning (CML) by signing up for a 60 day trial , or test drive CDP. If you are interested in chatting about how to manage the full data lifecycle with CDP, let your account team know or contact us directly.

Data Analytics 81

Data Analytics Retail Machine Learning Recruitment 81

Data Engineering Podcast

MAY 19, 2019

Summary In recent years the traditional approach to building data warehouses has shifted from transforming records before loading, to transforming them afterwards. The data build tool (dbt) is designed to bring battle tested engineering practices to your analytics pipelines.

Data Analytics 100

Data Analytics Building Engineering Data Warehouse 100

Knowledge Hut

FEBRUARY 7, 2023

The study of examining unprocessed data to draw inferences about such information is known as data analytics. Many data analytics methods and procedures have been mechanized into mechanical procedures and algorithms that operate on raw data for human consumption. This is the most frequently asked question.

Data Analytics 52

Data Analytics Business Analyst Raw Data Data Analysis 52

Rockset

JULY 29, 2022

Enterprise data warehouses (EDWs) became necessary in the 1980s when organizations shifted from using data for operational decisions to using data to fuel critical business decisions. Data warehouses are popular because they help break down data silos and ensure data consistency.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. Data storage and compute are very much the foundation of your data platform. Let’s jump in! So, let’s take a look at each in a bit more detail.

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Striim

FEBRUARY 10, 2023

trillion through investment in real-time data analytics. From telecommunication to retail, businesses are harnessing the power of data analytics to optimize operations and drive growth. Striim is a data integration platform that connects data from different applications and services to deliver real-time data analytics.

Data Analytics 52

Data Analytics Telecommunication Insurance Google Cloud 52

Cloudera

MAY 30, 2024

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses.

Data Lake 63

Data Lake Data Warehouse Programming Language Data Ingestion 63

Seattle Data Guy

FEBRUARY 10, 2024

Photo by Tiger Lily Data warehouses and data lakes play a crucial role for many businesses. It gives businesses access to the data from all of their various systems. As well as often integrating data so that end-users can answer business critical questions.

Data Lake 162

Data Lake Data Warehouse Data Accessible 162

Christophe Blefari

MARCH 1, 2023

dbt Core is an open-source framework that helps you organise data warehouse SQL transformation. dbt Core has been developed by dbt Labs, which was previously named Fishtown Analytics. dbt was born out of the analysis that more and more companies were switching from on-premise Hadoop data infrastructure to cloud data warehouses.

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Data Warehouse SQL Metadata Raw Data 278

Towards Data Science

MARCH 23, 2023

The difference between tables and views and how to use them Continue reading on Towards Data Science »

Data Warehouse 75

Data Warehouse Data Science Data Cloud Computing 75

Rockset

MARCH 10, 2022

This means that updates are inserted into a different location or you’re forced to rewrite old and new data to store it properly. Immutable data stores have been useful in certain analytics scenarios. Analytical queries could be accelerated by caching heavily-accessed read-only data in RAM or SSDs.

Data Analytics 52

Data Analytics Data Warehouse Medical MySQL 52

Propel Data

JANUARY 10, 2023

Create and query an API on top of your Snowflake data warehouse using Propel’s blazing-fast Serverless Analytics API Platform

Data Analytics 72

Data Analytics Building Data Warehouse Data 72

AltexSoft

MAY 14, 2021

And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Databand.ai

DECEMBER 20, 2022

The Top Data Analytics and Science Influencers and Content Creators on LinkedIn Ryan Yackel 2022-12-20 11:06:32 If you’re looking to brush up on all things data analytics and science, then LinkedIn certainly has no shortage of content. On LinkedIn, he posts regularly about data analytics and data science.

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52

Data Engineering Weekly

MAY 26, 2024

[link] Sponsored: From 90-sec queries to sub-second with DoubleCloud Learn how LSports, a top provider of real-time sports data, improved its data analytics using DoubleCloud’s Managed ClickHouse. seconds, enhancing real-time sports data analytics efficiency! and why one prefer dataframe over sql.

Data Engineering 57

Data Engineering Data Engineer Engineering Google Cloud 57

Towards Data Science

DECEMBER 23, 2023

Table of contents Understanding the building blocks Setting up Docker Desktop Configuring MinIO Getting started with JupyterLab Data pipeline: The ETL process Analysing semi-structured data Cleanup of resources Understanding the building blocks This tutorial involves a range of technologies. format("parquet").save("s3a://mybucket/country_trnsfm_data.parquet")

SQL 73

SQL Data Analytics Hadoop Raw Data 73

Knowledge Hut

APRIL 25, 2024

If you want to stay ahead of the curve, you need to be aware of the top big data technologies that will be popular in 2024. This article will discuss big data analytics technologies, technologies used in big data, and new big data technologies. What Are Big Data T echnologies?

Big Data 98

Big Data Technology NoSQL Hadoop 98

Advancing Analytics: Data Engineering

JUNE 21, 2019

Hear me out – back in the on-premises days we had data loading processes that connect directly to our source system databases and perform huge data extract queries as the start of one long, monolithic data pipeline, resulting in our data warehouse. Are you still bound by source-system access? Till next time.

Data Warehouse 52

Data Warehouse Business Intelligence Data Data Validation 52

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 42

Data Warehouse Relational Database Hadoop BI 42

ProjectPro

JUNE 24, 2021

According to Gartner , organizations can suffer a financial loss of up to 15 million dollars for the poor quality of data. As per McKinsey , 47% of organizations believe that data analytics has impacted the market in their respective industries. This number grew to 67.9% as of 2018, and is only increasing from there.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

Propel Data

MARCH 14, 2023

Learn how to set up Segment for your web application and store the captured data in Snowflake, a popular data warehouse solution.

Data Analytics 52

Data Analytics Data Warehouse Building Data 52

Christophe Blefari

JANUARY 20, 2024

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. My advice on this point is to learn from others.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Christophe Blefari

DECEMBER 30, 2022

Analytics engineers provide clean data sets to end users, modeling data in a way that empowers end users to answer their own questions. [.], an analytics engineer spends their time transforming, testing, deploying, and documenting data. 1 Analytics Engineering brought back light on data modeling.

Data Warehouse 130

Data Warehouse BI Data Machine Learning 130

Data Engineering Podcast

DECEMBER 25, 2022

Summary Encryption and security are critical elements in data analytics and machine learning applications. We have well developed protocols and practices around data that is at rest and in motion, but security around data in use is still severely lacking. or any other destination you choose. Pricing for SQLake is simple.

Machine Learning 130

Machine Learning Systems Data Lake Data Warehouse 130

ProjectPro

MAY 13, 2016

As the appetite for Hadoop and related big data technologies grows at an exponential rate, it is not out to spell the death of data warehousing. Data warehousing as a technology is evolving. Data Warehouse – Decide Which One to Use When Hadoop vs DataWarehouse Shocking Headlines like “Is data warehouse dead?”,

Data Warehouse 40

Data Warehouse Hadoop Unstructured Data Big Data 40

Towards Data Science

JANUARY 16, 2024

Evolution of the data landscape 1980s — Inception Relational databases came into existence. Databases were overwhelmed with transactional and analytical workloads. Result: Data warehouse was born. Image by the author Early 1990s — Scale Analytical workloads started to get complex. Data volumes started to grow.

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Data Warehouse Data Architecture Relational Database NoSQL 65