Data Engineering Podcast

DECEMBER 16, 2019

You work hard to make sure that your data is clean, reliable, and reproducible throughout the ingestion pipeline, but what happens when it gets to the data warehouse? Dataform picks up where your ETL jobs leave off, turning raw data into reliable analytics. How is the metadata itself stored and managed in Marquez?

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

Workfall

JULY 4, 2023

Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights. With DBT, they weave powerful SQL spells to create data models that capture the essence of their organization’s information. The data warehouse, role, database, schema, credentials, etc.

Data Warehouse 69

Data Warehouse SQL PostgreSQL Database 69

Monte Carlo

FEBRUARY 15, 2023

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. What is a data warehouse? What’s the difference between a transactional database and a data warehouse?

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Knowledge Hut

JANUARY 11, 2024

You may learn the following programming languages: Python C, C++ Java MATLAB Step 3: Develop database skills Databases are used to retrieve and store data in organizations. This work is done by financial data scientists. You must know how to work with a variety of Relational Database Management Systems (RDBMS).

Finance 93

Finance Data Science Programming Language Machine Learning 93

Knowledge Hut

JUNE 16, 2023

Analyzing data with statistical and computational methods to conclude any information is known as data analytics. Finding patterns, trends, and insights, entails cleaning and translating raw data into a format that can be easily analyzed. They then arrange the data in a suitable format that is simple to understand.

Programming Language 52

Programming Language Cloud Computing Data Preparation Data Science 52

ProjectPro

FEBRUARY 8, 2023

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses.

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

APRIL 19, 2023

The process of gathering and compiling data from various sources is known as data Aggregation. Businesses and groups gather enormous amounts of data from a variety of sources, including social media, customer databases, transactional systems, and many more. This can be done manually or with a data cleansing tool.

Process 59

Process Data Mining Aggregated Data Portfolio 59

Rockset

AUGUST 30, 2021

It becomes prohibitively complex and expensive to use a data warehouse to serve real-time analytics. Rockset is a real-time analytics database in the cloud that uses an indexing approach to deliver low-latency analytics at scale. That is sufficient for some use cases.

SQL 52

SQL Kafka MongoDB MySQL 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. That needs to be done because raw data is painful to read and work with. Ability to demonstrate expertise in database management systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

FEBRUARY 16, 2023

If you are still wondering whether or why you need to master SQL for data engineering, read this blog to take a deep dive into the world of SQL for data engineering and how it can take your data engineering skills to the next level. Data engineers can perform any quality checks using the DDL commands in SQL.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

Knowledge Hut

NOVEMBER 28, 2023

Java can be used to build APIs and move them to destinations in the appropriate logistics of data landscapes. Cloud Data engineering is all about designing, programming, and testing software, which is required for modern database solutions. ETL is central to getting your data where you need it.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

U-Next

AUGUST 3, 2022

Data transformation: Data Scientists carry out data transformation after collecting the data. For the computer to function effectively during the analysis process, this conversion involves changing the structure and content of the raw data. Non-Technical Competencies.

Retail 52

Retail Data Science Computer Science Entertainment 52

Rockset

JANUARY 10, 2019

This post outlines how to use SQL for querying and joining raw data sets like nested JSON and CSV - for enabling fast, interactive data science. Data scientists and analysts deal with complex data. Much of what they analyze could be third-party data, over which there is little control.

Data Science 40

Data Science SQL Relational Database Raw Data 40

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). There is a large amount of data involved.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Confluent

OCTOBER 24, 2019

The blue parts represent PostgreSQL databases, and turquoise is a Nginx web server. The command handler has two external connections to Kafka and PostgreSQL. To connect to PostgreSQL, next-jdbc provides low-level access from Clojure to JDBC-based databases. Clojure command handler. Rust libraries for Kafka.

Kafka 17

Kafka Java Banking Bytes 17

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). Wrangling the data.

Kafka 19

Kafka Building Data Coding 19

ProjectPro

AUGUST 21, 2015

Data that can be stored in traditional database systems in the form of rows and columns, for example, the online purchase transactions can be referred to as Structured Data. Data that can be stored only partially in traditional database systems, for example, data in XML records can be referred to as semi-structured data.

Hadoop 40

Hadoop Big Data Metadata Java 40