Pickl AI

APRIL 6, 2023

In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Sound knowledge of relational databases or NoSQL databases like Cassandra. This includes Database System Management (SQL or Non-SQL), Data Warehousing, Machine Learning, programming basics, and ETL.

Azure 52

Azure Data Engineering Data Engineer Data Engineering 52

Becoming Human

JANUARY 23, 2023

Let’s understand with an example if we consider web development so there are UI , UX , Database , Networking , and Servers and for implementing all these things we have different-different tools - technologies and frameworks , and when we have done with these things we just called this process as web development.

Data Science 105

Data Science Big Data Big Data Deep Learning 105

The MLOps Blog

JANUARY 23, 2023

But, it is not rare that data engineers and database administrators process, control, and store terabytes of data in projects that are not related to machine learning. Data from different formats, databases, and sources are combined together for modeling. Basically, every machine learning project needs data. DVC Git LFS neptune.ai

ML 52

ML ML Data Lakes Machine Learning 52

Smart Data Collective

MAY 20, 2019

With databases, for example, choices may include NoSQL, HBase and MongoDB but its likely priorities may shift over time. For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. The popular tools, on the other hand, include Power BI, ETL, IBM Db2, and Teradata.

Analytics 111

Analytics Analytics Data Analyst Machine Learning 111

Mlearning.ai

MAY 16, 2023

ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

NOVEMBER 15, 2023

Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible. Unlike traditional databases that require a predefined schema, Data Lakes accommodate both structured and unstructured data. Here it becomes important to highlight the database systems.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

phData

FEBRUARY 5, 2024

Creating the databases, schemas, roles, and access grants that comprise a data system information architecture can be time-consuming and error-prone. Replicate can interact with a wide variety of databases, data warehouses, and data lakes (on-premise or based in the cloud).

SQL 52

SQL Database Data Quality Data Warehouse 52

Mlearning.ai

JULY 10, 2023

In my 7 years of Data Science journey, I’ve been exposed to a number of different databases including but not limited to Oracle Database, MS SQL, MySQL, EDW, and Apache Hadoop. Tables inherent the key characteristics of its platform BigQuery which provides an upper hand over traditional databases.

SQL 52

SQL Database Apache Hadoop Data Science 52

IBM Journey to AI blog

JANUARY 18, 2023

While traditional data warehouses made use of an Extract-Transform-Load (ETL) process to ingest data, data lakes instead rely on an Extract-Load-Transform (ELT) process. This adds an additional ETL step, making the data even more stale. data platforms and databases), all interacting with one another to provide greater value.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Dataconomy

FEBRUARY 23, 2023

This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently. Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data.

Data Engineering 91

Data Engineering Data Engineer Data Engineering Data Engineering 91

The MLOps Blog

MAY 31, 2023

So, a better database architecture would be to maintain multiple tables where one of the tables maintains the past 3 months history with session-level details, whereas other tables may contain weekly aggregated click, ATC, and order data. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data.

ML 59

ML ML Algorithm Machine Learning 59

IBM Journey to AI blog

SEPTEMBER 25, 2023

The evolution of Presto at Uber Beginning of a data analytics journey Uber began their analytical journey with a traditional analytical database platform at the core of their analytics. They stood up a file-based data lake alongside their analytical database. Uber has made the Presto query engine connect to real-time databases.

Data Lakes 94

Data Lakes Analytics Analytics Clustering 94