Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Alation

MARCH 1, 2022

Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

DagsHub

AUGUST 23, 2024

We already know that a data quality framework is basically a set of processes for validating, cleaning, transforming, and monitoring data. Data Governance Data governance is the foundation of any data quality framework. It primarily caters to large organizations with complex data environments.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Apache Spark A fast, in-memory data processing engine that provides support for various programming languages, including Python, Java, and Scala. Data Warehousing Solutions Tools like Amazon Redshift, Google BigQuery, and Snowflake enable organisations to store and analyse large volumes of data efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

MAY 7, 2024

Their tasks encompass: Data Collection and Extraction Identify relevant data sources and gather data from various internal and external systems Extract, transform, and load data into a centralized data warehouse or analytics platform Data Cleaning and Preparation Cleanse and standardize data to ensure accuracy, consistency, and completeness.

Data Analyst 52

Data Analyst Tableau Data Science Data Analysis 52

ODSC - Open Data Science

JANUARY 18, 2024

Data scientists typically have strong skills in areas such as Python, R, statistics, machine learning, and data analysis. Believe it or not, these skills are valuable in data engineering for data wrangling, model deployment, and understanding data pipelines.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JULY 3, 2023

Explore their features, functionalities, and best practices for creating reports, dashboards, and visualizations. Develop programming skills: Enhance your programming skills, particularly in languages commonly used in BI development such as SQL, Python, or R.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

Pickl AI

JULY 29, 2024

Data Governance and Security Hadoop clusters often handle sensitive data, making data governance and security a significant concern. Ensuring compliance with regulations such as GDPR or HIPAA requires implementing robust security measures, including data encryption, access controls, and auditing capabilities.

Hadoop 52

Hadoop Clustering Big Data Big Data 52

The MLOps Blog

MARCH 15, 2023

Data governance: Ensure that the data used to train and test the model, as well as any new data used for prediction, is properly governed. For small-scale/low-value deployments, there might not be many items to focus on, but as the scale and reach of deployment go up, data governance becomes crucial.

AWS 52

AWS ETL ML ML 52

Data Science Blog

SEPTEMBER 3, 2024

Celonis versucht Machine Learning innerhalb der Plattform aus einer Hand anzubieten und hat auch eigene Python-Bibleotheken dafür entwickelt. Alternativ zu Databricks können auch andere Data Warehouse Datenbankplattformen zur Anwendung kommen, beispielsweise auch snowflake mit dbt. Bisher dreht sich hier viel eher noch um z.

Data Science 130

Data Science Power BI Azure Data Warehouse 130