Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

JANUARY 25, 2023

In an evolving data landscape, the explosion of new tooling solutions—from cloud-based transforms to data observability —has made the question of “build versus buy” increasingly important for data leaders. Hint: it’s not a one-size-fits-all answer, but answering a few critical questions can help. Let’s jump in!

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Monte Carlo

FEBRUARY 26, 2024

A data catalog is a constantly updated inventory of the universe of data assets within an organization. It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems.

Metadata 52

Metadata Government Data Data Governance 52

AltexSoft

AUGUST 22, 2022

What’s more, Gartner identifies data fabric implementation as one of the top strategic technology trends for 2022 and expects that by 2024, data fabric deployments will increase the efficiency of data use while halving human-driven data management tasks. What is data fabric? How data fabric works.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Architecture 124

Architecture Metadata Government Kafka 124

ProjectPro

FEBRUARY 16, 2023

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. AWS Glue has a central metadata repository called the Glue catalog.

AWS 52

AWS Data Management ETL Tools Management 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Data Engineering Podcast

JULY 1, 2018

Cheryl Martin, Chief Data Scientist for Alegion, discusses the importance of properly labeled information for machine learning and artificial intelligence projects, the systems that they have built to scale the process of incorporating human intelligence in the data preparation process, and the challenges inherent to such an endeavor.

Metadata 100

Metadata Machine Learning Data Preparation Data Collection 100

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 110

IT Unstructured Data Data Architecture Government 110

Rockset

DECEMBER 17, 2021

We had chosen Retool to build the UI, as we wanted something fast and simple instead of deploying our own web stack. With Retool, you can build a fully functional UI with tables, filter controls, etc. James is the CEO and Founder of Omnata , a tech startup building data integration for the modern data stack.

SQL 52

SQL NoSQL Database Design Metadata 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Snowflake

JULY 10, 2023

Processing files in a Python UDF and Stored Procedure has piqued the interest of our data scientists and paves the way for automation of new, complex data pipelines.” Mike Tuck, Air Pollution Specialist Why unstructured data?

Unstructured Data 40

Unstructured Data Python Process Scala 40

Rockset

APRIL 26, 2023

To learn more about how to build fraud detection models, this is a great resource. Data lake : Additionally, anomaly scores are fed to a data lake for durable storage and visualization. Occupancy sensors help businesses understand usage patterns across buildings, floors, and meeting rooms.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

AltexSoft

JUNE 7, 2021

HDFS master-slave structure. A HDFS Master Node, called a NameNode , keeps metadata with critical information about system files (like their names, locations, number of data blocks in the file, etc.) and keeps track of storage capacity, a volume of data being transferred, etc. Data management and monitoring options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JANUARY 24, 2023

It is a popular ETL tool well-suited for big data environments and extensively used by data engineers today to build and maintain data pipelines with minimal effort. You can leverage AWS Glue to discover, transform, and prepare your data for analytics.

AWS 52

AWS Data Lake ETL Tools Scala 52

Data Engineering Podcast

FEBRUARY 3, 2019

In this episode Eric Kansa describes how they process, clean, and normalize the data that they host, the challenges that they face with scaling ETL processes which require domain specific knowledge, and how the information contained in connections that they expose is being used for interesting projects.

Digital Media 100

Digital Media Media PostgreSQL Datasets 100

Monte Carlo

APRIL 1, 2021

is whether to choose a data warehouse or lake to power storage and compute for their analytics. While data warehouses provide structure that makes it easy for data teams to efficiently operationalize data (i.e., Data discovery tools and platforms can help. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Ascend.io

JULY 19, 2023

For one, data mesh tackles the real headaches caused by an overburdened data lake and the annoying game of tag that’s too often played between the people who make data, the ones who use it, and everyone else caught in the middle. Establish standardized processes and guidelines for curating data products.

Data Governance 40

Data Governance Government Metadata Data 40

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

SQL 72

SQL Data Analytics Hadoop Raw Data 72

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Works with only structured data. Hardware Hadoop uses commodity hardware.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 83

Engineering Raw Data Data Science Scala 83

Rockset

AUGUST 2, 2023

To support this, Windward’s data platform needed to enable rapid iteration so they could quickly innovate and build more AI capabilities. The Windward Maritime AI platform Lastly, Windward wanted to move their entire platform from batch-based data infrastructure to streaming.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Precisely

OCTOBER 5, 2023

When we think about the big picture of data integrity – that’s data with maximum accuracy, consistency, and context – it becomes abundantly clear why data enrichment is one of its six key pillars (along with data integration, data observability, data quality, data governance, and location intelligence).

Raw Data 67

Raw Data Insurance Datasets Telecommunication 67

Cloudera

SEPTEMBER 17, 2020

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Events or time-series data served by our real-time events or time-series data store solutions.

Unstructured Data 81

Unstructured Data Data Warehouse Pharmaceutical MySQL 81

AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

NOVEMBER 15, 2021

It even allows you to build a program that defines the data pipeline using open-source Beam SDKs (Software Development Kits) in any three programming languages: Java, Python, and Go. With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

JULY 18, 2023

With its native support for in-memory distributed processing and fault tolerance, Spark empowers users to build complex, multi-stage data pipelines with relative ease and efficiency. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Big Data 52

Big Data Data Process Process Hadoop 52

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Data Engineering Weekly

MARCH 24, 2023

The data engineers say these are the prime concerns in the data creation process. Lack of Data Modeling Schema Breaking Changes Data Quality Schemata build from the ground as a data-modeling-first, data-contract-driven platform. However, Event sourcing comes with a few major limitations.

Engineering 67

Engineering Data Transportation Database 67

Monte Carlo

NOVEMBER 20, 2023

As your datasets start to grow beyond what can be manually inspected, there’s a transition to using dbt for more structured data testing. Column-level tests are manually added to validate data integrity and ensure specific data quality standards. When you’re at this level, it’s time to start walking.

Government 69

Government Data Data Governance Datasets 69

ProjectPro

JANUARY 31, 2022

Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Snowflake Features that Make Data Science Easier Building Data Applications with Snowflake Data Warehouse Snowflake Data Warehouse Architecture How Does Snowflake Store Data Internally? What Does Snowflake Do?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

Databand.ai

NOVEMBER 4, 2022

How Databand can help Databand empowers data platform teams to deliver reliable and trustworthy data. In other words, it allows you to catch bad data before it impacts your business.

Data 52

Data Data Pipeline Retail Metadata 52