Azure Data Engineering

MAY 15, 2022

When it comes to transforming structured data, (e.g., stored in a database, SQL is the most convenient and fit-to-purpose option. Stored procedures provide a way to store the transformation logic as a set of SQL statements that can be re-executed as pre-compiled code. applying business logic, standardization etc.)

SQL 130

SQL Database Structured Data Data 130

ThoughtSpot

MARCH 5, 2024

Snowflake dynamic tables are a special type of table that automatically updates based on a defined SQL query. When created, Snowflake materializes query results into a persistent table structure that refreshes whenever underlying data changes. What are dynamic tables? How to connect ThoughtSpot to Snowflake dynamic tables: 1.

BI 94

BI Datasets Raw Data SQL 94

Rockset

JULY 6, 2022

Typically stored in SQL statements, the schema also defines all the tables in the database and their relationship to each other. Companies carefully engineered their ETL data pipelines to align with their schemas (not vice-versa). SQL queries were easier to write. They also ran a lot faster. There were heavy tradeoffs, though.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Christophe Blefari

JANUARY 14, 2024

What I would do differently getting into Data Engineering — Data engineering has changed a lot in the recent years and Daniel gives 3 advices that you should consider to get into data engineering. Learn SQL, be social and learn to say no. Every data transform is technical debt. How Monzo built Year in Monzo.

Google Cloud 130

Google Cloud Data SQL Python 130

Rockset

FEBRUARY 21, 2019

Which is a great reason for Rockset to support SQL queries on PDF files, in our mission to make data more usable to everyone. Now add PDFs to the mix, and users can combine PDF data with data of other formats, from various sources, into their SQL analyses.

SQL 52

SQL Metadata Structured Data IT 52

Knowledge Hut

MAY 2, 2024

It also supports a rich set of higher-level tools, including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala, Python, and R and an optimized engine that supports general execution graphs.

Java 98

Java Hadoop Scala SQL 98

Data Engineering Weekly

APRIL 7, 2024

VCs have moved on from data catalogs, yet practitioners told me they look forward to solving data discovery. link] Pinterest: How we built Text-to-SQL at Pinterest Last week Intuit shared its key learning building Text 2 SQL , and Pinterest publishes the tech deep dive on how its internal Text2SQL work.

Data Engineering 70

Data Engineering Data Engineer Engineering Unstructured Data 70

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

DECEMBER 26, 2023

Certain roles like Data Scientists require a good knowledge of coding compared to other roles. Data Science also requires applying Machine Learning algorithms, which is why some knowledge of programming languages like Python, SQL, R, Java, or C/C++ is also required.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Rockset

JULY 9, 2019

One of the main hindrances to getting value from our data is that we have to get data into a form that’s ready for analysis. Consider the hoops we have to jump through when working with semi-structured data, like JSON, in relational databases such as PostgreSQL and MySQL. It sounds simple, but it rarely is.

Relational Database 40

Relational Database PostgreSQL MySQL Database 40

Knowledge Hut

APRIL 23, 2024

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

FEBRUARY 29, 2024

Learning inferential statistics website: wallstreetmojo.com, kdnuggets.com Learning Hypothesis testing website: stattrek.com Start learning database design and SQL. A database is a structured data collection that is stored and accessed electronically. Considering this information database model is fitted with data.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

Knowledge Hut

APRIL 23, 2024

It uses data from the past and present to make decisions related to future growth. Data Type Data science deals with both structured and unstructured data. Business Intelligence only deals with structured data. It is not as flexible as BI data sources always have to be pre-planned.

Business Intelligence 52

Business Intelligence Data Science BI Unstructured Data 52

Knowledge Hut

MAY 2, 2024

It also supports a rich set of higher-level tools, including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. It provides high-level APIs in Java, Scala, Python, and R and an optimized engine that supports general execution graphs.

Hadoop 52

Hadoop Java Scala Programming Language 52

Cloudera

JUNE 3, 2022

First of all, there’s the question of what data is currently available within their organization, where it is, and how it can be accessed. Data scientists might want to do some SQL – based profiling, or visualize the data to better understand the distributions, veracity, and hidden nuances. Next Steps.

Data Analysis 88

Data Analysis PostgreSQL Data Science SQL 88

Edureka

AUGUST 2, 2023

R’s popularity in the data science community is also evident through its active community support and continuous development of new packages and techniques. SQL Structured Query Language, or SQL, is used to manage and work with relational databases. Data scientists use SQL to query, update, and manipulate data.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

Knowledge Hut

MARCH 27, 2024

An ordered set of data kept in a computer system and typically managed by a database management system (DBMS) is called a database. Table modeling of the data in standard databases facilitates efficient searching and processing. SQL, or structured query language, is widely used for writing and querying data.

Database 52

Database Algorithm Relational Database PostgreSQL 52

Knowledge Hut

JANUARY 29, 2024

In contrast, ETL is primarily employed by DW/ETL developers responsible for data integration between source systems and reporting layers. Data Structure: Data wrangling deals with varied and complex data sets, which may include unstructured or semi-structured data. Frequently Asked Questions (FAQs) 1.

Raw Data 52

Raw Data Data Mining Data Preparation Structured Data 52

Striim

MAY 1, 2024

This platform acts as the primary structured data repository in Google Cloud. Concurrently, SQL Server data is thoroughly cleaned in Link Data, which also extracts images and email attachments from different systems, ensuring data integrity and availability.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

Knowledge Hut

APRIL 25, 2023

It is one of the most liked data engineering tools of the present day. It allows data engineers to easily build and customize data models and create interactive dashboards and reports. Key features: Interactive data exploration Real-time reporting Easy data modeling 3.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Data Engineering Weekly

JUNE 4, 2023

[link] Policy Genius: Data Warehouse Testing Strategies for Better Data Quality Data Testing and Data Observability are widely discussed topics in Data Engineering Weekly. Can we test SQL business logic during the development phase itself? Perhaps unit test the pipeline?

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights. In DBT, transformations are like these artisans.

Data Warehouse 69

Data Warehouse SQL PostgreSQL Database 69

phData: Data Engineering

SEPTEMBER 19, 2023

Before diving into the data models for data lakes, let’s look at the difference between a data warehouse and a data lake. There are tools designed specifically to analyze your data lake files, determine the schema, and allow for SQL statements to be run directly off this data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Data Engineering Podcast

AUGUST 31, 2020

Your host is Tobias Macey and today I’m interviewing Eldad Farkash about Firebolt, a cloud data warehouse optimized for speed and elasticity on structured and semi-structured data Interview Introduction How did you get involved in the area of data management?

Data Warehouse 100

Data Warehouse Cloud Building Data Lake 100

Rockset

MARCH 24, 2022

It’s difficult to create data analytics systems that can easily do this while maintaining fast query performance and real-time capabilities. It’s even harder to do this without constantly updating your data ops in some way. Rockset ingests semi-structured and nested data without the need to specify a schema or denormalize data.

Non-relational Database 52

Non-relational Database Relational Database Database Data Pipeline 52

U-Next

MARCH 1, 2023

Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. What is AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Knowledge Hut

DECEMBER 26, 2023

If you are looking for a wholesome list of books, including one like statistics for data science book or even the best python data science books, you can refer to the below list:- 1. Programming Programming is crucial to have an in-depth understanding of data science.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is used for data science, meaning that we utilize the capabilities of this NoSQL database system as part of our data analysis and data modeling processes, which fall under the realm of data science. There are several benefits to MongoDB for data science operations.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Excel, SharePoint, and web services.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Knowledge Hut

DECEMBER 21, 2023

HIVE Hive is an open-source data warehousing Hadoop tool that helps manage huge dataset files. Hive can run queries like SQL, known as HQL or Hive Query Language. Features: It uses queries that are similar to those of SQL. There are built-in functions used for data mining and other related works. Hive has high latency.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

ProjectPro

SEPTEMBER 9, 2021

Spark SQL, for instance, enables structured data processing with SQL. Highly flexible and scalable Real-time stream processing Spark Stream – Extension of Spark enables live-stream from massive data volumes from different web sources. Hive uses HQL, while Spark uses SQL as the language for querying the data.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Ascend.io

FEBRUARY 28, 2024

Read More: AI Data Platform: Key Requirements for Fueling AI Initiatives How Data Engineering Enables AI Data engineering is the backbone of AI’s potential to transform industries , offering the essential infrastructure that powers AI algorithms. Tools like GitHub Copilot exemplify this trend.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Rockset

NOVEMBER 5, 2021

Writing SQL against an RDS instance was just impossible,” Pattamatta said. Solution 2: Ingest Dynamic, Semi-Structured Data Rockset supports schemaless ingestion of raw semi-structured data. By adopting Rockset, DataBrain didn’t need to hire a data engineer just to manage ETL scripts.

PostgreSQL 52

PostgreSQL Structured Data Data Lake Data Ingestion 52

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? create function pdf_read(file_url string) returns variant language python runtime_version=3.8

Unstructured Data 40

Unstructured Data Python Process Scala 40

Data Engineering Podcast

DECEMBER 8, 2019

Links SnowflakeDB Free Trial Stack Overflow Data Warehouse Oracle DB MPP == Massively Parallel Processing Shared Nothing Architecture Multi-Cluster Shared Data Architecture Google BigQuery AWS Redshift AWS Redshift Spectrum Presto Podcast Episode SnowflakeDB Semi-Structured Data Types Hive ACID == Atomicity, Consistency, Isolation, Durability 3rd Normal (..)

Data Warehouse 100

Data Warehouse Cloud AWS Relational Database 100

Rockset

JULY 28, 2022

This means analysts who are used to using SQL will have a steep learning curve for this new language. Documents in MongoDB can also have complex structures. Rockset’s search capability is also SQL based, which again might reduce the burden of producing search queries as both Elasticsearch and MongoDB use bespoke languages.

MongoDB 52

MongoDB Kafka NoSQL Data Lake 52

Rockset

OCTOBER 21, 2022

We’ll integrate with Kafka and S3 through Rockset’s data connectors. This allows Rockset to automatically ingest and index JSON i.e.nested semi-structured data without flattening it. From there, we’ll create data APIs that’ll be used in Retool (step 4). When you do this, you’ll see the preview.

Kafka 52

Kafka Building SQL Database 52