Ascend.io

MAY 24, 2023

This article is based on a presentation given by Sarwat Fatima , Principal Data Engineer at Biome Analytics, at the Data Pipeline Automation Summit 2023. The question then arises: how can we efficiently manage and process this ever-growing mountain of data to uncover the value it holds? Reading not your thing?

Healthcare 52

Healthcare Data Pipeline Hospitality Datasets 52

Pinterest Engineering

MAY 2, 2023

We set up a separate dataset for each event type indexed by our system, because we want to have the flexibility to scale these datasets independently. In particular, we wanted our KV store datasets to have the following properties: Allows inserts. We need each dataset to store the last N events for a user.

Lambda Architecture 66

Lambda Architecture Datasets Software Engineer Software Engineering 66

Striim

NOVEMBER 8, 2023

With the help of Striim’s enterprise-grade platform, companies can now deploy and manage a data mesh architecture with automated data mapping, cloud-native capabilities, and real-time analytics. Data as a product This principle can be summarized as applying product thinking to data.

Architecture 52

Architecture Generalist Government Datasets 52

Workfall

SEPTEMBER 18, 2023

Streamline Data Volume for Efficiency: While Snowflake is capable of handling large datasets, it’s essential to be mindful of data volume. Focus on sending relevant, necessary data to Snowflake to prevent overwhelming the integration process. Account for potential changes in data schemas and structures.

Data Pipeline 93

Data Pipeline Raw Data Data Schemas Healthcare 93

Netflix Tech

OCTOBER 27, 2020

Netflix Scheduler is built on top of Meson which is a general purpose workflow orchestration and scheduling framework to execute and manage the lifecycle of the data workflow. Bulldozer makes data warehouse tables more accessible to different microservices and reduces each individual team’s burden to build their own solutions.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Monte Carlo

OCTOBER 11, 2022

Imagine this You’re a data scientist with a swagger working on a predictive model to optimize a fast-growing company’s digital marketing spend. After diligent data exploration, you import a few datasets into your Python notebook. Model design You see the LinkedIn ad click data has.1% Image courtesy of Chad Sanderson.

IT 52

IT Datasets Data Warehouse Data Analysis 52

Rockset

MARCH 31, 2022

On top of that, I had to make that data available to our custom-built application via a secure RESTful endpoint with a less than one second response time. By day three of my new job at Sounding Board, I was able to meet those requirements, build, and demonstrate a real-time, reporting and analytics application using Rockset and Retool.

MongoDB 52

MongoDB Data Architect Data Schemas SQL 52

Rockset

SEPTEMBER 20, 2022

This blog discusses some emerging use cases for real-time blockchain analytics and some key considerations for developers building dApps. On-chain data has to be tied back to relevant off-chain datasets, which can require complex JOIN operations which lead to increased data latency.

PostgreSQL 52

PostgreSQL MongoDB SQL Datasets 52

Monte Carlo

FEBRUARY 26, 2024

Alation’s Open Data Quality Initiative allows smooth data sharing between sources. Alteryx Connect Alteryx Connect data catalog. With Alteryx , you can create workflows without needing to code by using the provided automation building blocks. With Ataccama, AI detects related and duplicate datasets.

Metadata 52

Metadata Government Data Data Governance 52

Knowledge Hut

OCTOBER 4, 2023

Data Source Connectivity Power BI requirements support a large range of data sources, which can be connected to an app to build a dataflow to aggregate, analyze, and visualize data. Some of the supported data sources are, 1. All Under Get data, you can view the available data connection.

BI 52

BI Systems Raw Data Business Intelligence 52

Monte Carlo

MAY 31, 2022

It involves a contract with the client sending the data , schema registry, and pipeline owners responsible for fixing any issues. Challenge: Building Trust with the Business On the heels of this organizational shift, Lior started prioritizing building data trust and availability a cross the entire organization.

BI 52

BI Data Warehouse Unstructured Data Data Schemas 52

Knowledge Hut

MARCH 22, 2024

Versatility: The versatile nature of MongoDB enables it to easily deal with a broad spectrum of data types , structured and unstructured, and therefore, it is perfect for modern applications that need flexible data schemas. Extracting, transforming, and loading data from various sources into MongoDB.

MongoDB 52

MongoDB Amazon Web Services Computer Science Education 52

ProjectPro

NOVEMBER 22, 2021

What's the difference between an RDD, a DataFrame, and a DataSet? RDDs contain all datasets and dataframes. If a similar arrangement of data needs to be calculated again, RDDs can be efficiently reserved. It's useful when you need to do low-level transformations, operations, and control on a dataset. count())) df2.show(truncate=False)

Hadoop 52

Hadoop Python Datasets Metadata 52

Booking.com Engineering

DECEMBER 2, 2022

BigQuery also offers native support for nested and repeated data schema[4][5]. We take advantage of this feature in our ad bidding systems, maintaining consistent data views from our Account Specialists’ spreadsheets, to our Data Scientists’ notebooks, to our bidding system’s in-memory data.

Systems 52

Systems Cloud MySQL Relational Database 52

AltexSoft

OCTOBER 3, 2022

A triple is the most basic knowledge graph model you can build with two nodes and one edge explaining their connection. They allow for representing various types of data and content (data schema, taxonomies, vocabularies, and metadata) and making them understandable for computing systems. A knowledge graph example.

Relational Database 52

Relational Database Banking Media Computer Science 52

ProjectPro

JANUARY 31, 2023

MapReduce is a Hadoop framework used for processing large datasets. Another name for it is a programming model that enables us to process big datasets across computer clusters. This program allows for distributed data storage, simplifying complex processing and vast amounts of data. What is MapReduce in Hadoop?

Big Data 52

Big Data Hadoop AWS Relational Database 52

dbt Developer Hub

FEBRUARY 7, 2022

Jaffle Shop is a demo repo referenced in dbt’s Getting Started Guide , and its jaffles hold a special place in the dbt community’s hearts, as well as on Data Twitter™. So, I thought it only apt to build on the collective reverence for these tasty, crunchy snacks to talk about customer 360 views. What's a customer 360? ​

Data Warehouse 52

Data Warehouse Datasets Data SQL 52

Knowledge Hut

DECEMBER 28, 2023

Compare and sync servers, data, schema, and other components of the database Transaction Rollback Functionality that mitigates the need for short-term backup. Key Features: Ability to navigate and manage specific database objects like tables and views.

SQL 52

SQL MySQL PostgreSQL Database 52

Cloud Academy

JANUARY 27, 2022

For example, it’s good to be familiar with the different data types in the field, including: variables varchar int char prime numbers int numbers Also, named pairs and their storage in SQL structures are important concepts. These fundamentals will give you a solid foundation in data and datasets.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Netflix Tech

OCTOBER 23, 2019

For example, while Python developers are used to working inside an environment constructed using a package manager with a relatively small number of dependencies, Scala developers typically work in a project-based environment with a build tool managing hundreds of (often) conflicting dependencies.

Scala 93

Scala Machine Learning Python Coding 93

Rockset

OCTOBER 6, 2022

Consequently, we needed a data backend with the following characteristics: Scale With ~50 commits per working day (and thus at least 50 pull request updates per day) and each commit running over one million tests, you can imagine the storage/computation required to upload and process all our data.

AWS 52

AWS Data Schemas Accessible Accessibility 52

Rockset

DECEMBER 9, 2021

Companies that embraced the modern data stack reaped the rewards, namely the ability to make even smarter decisions with even larger datasets. Now more than ten years old, the modern data stack is ripe for innovation. Real-time insights delivered straight to users, i.e. the modern real-time data stack.

Transportation 52

Transportation BI SQL Data Warehouse 52

dbt Developer Hub

NOVEMBER 28, 2021

We build a product based on the standards, conventions, and capabilities that are created there, and at least 70% of our engineering time is spent in contribution. Here are the tools I chose to use: Google Bigquery acts as the main database, holding all the source data, intermediate models, and data marts.

Raw Data 52

Raw Data Metadata Database Datasets 52

Monte Carlo

APRIL 20, 2023

This way no decisions get made on bad data and our team becomes a proactive part of the solution,” said then Senior Director of Data at Freshly, Vitaly Lilich. Data access and enablement Data lineage is essential to data quality, but that is far from its only use case. Analyze your current schema and lineage.

Data Warehouse 52

Data Warehouse BI Data Government 52

Monte Carlo

FEBRUARY 6, 2023

As you probably already know if you’re reading this, a data warehouse migration is the process of moving data from one warehouse to another. In the old days, data warehouses were bulky, on-prem solutions that were difficult to build and equally difficult to maintain. And how you plan for it is the first step to success.

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

Netflix Tech

OCTOBER 23, 2019

For example, while Python developers are used to working inside an environment constructed using a package manager with a relatively small number of dependencies, Scala developers typically work in a project-based environment with a build tool managing hundreds of (often) conflicting dependencies.

Scala 43

Scala Machine Learning Python Coding 43

Netflix Tech

OCTOBER 23, 2019

For example, while Python developers are used to working inside an environment constructed using a package manager with a relatively small number of dependencies, Scala developers typically work in a project-based environment with a build tool managing hundreds of (often) conflicting dependencies.

Scala 40

Scala Machine Learning Python Coding 40

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Hive requires a well-defined Schema. Language It is a procedural data flow language. Follows SQL Dialect and is a declarative language.

Hadoop 40

Hadoop Metadata SQL Database 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40