Towards AI

OCTOBER 31, 2024

Data analytics has become a key driver of commercial success in recent years. The ability to turn large data sets into actionable insights can mean the difference between a successful campaign and missed opportunities. Flipping the paradigm: Using AI to enhance data quality What if we could change the way we think about data quality?

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Data Quality Analytics Analytics Clean Data 122

Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

Pickl AI

JULY 24, 2024

Summary: Data quality is a fundamental aspect of Machine Learning. Poor-quality data leads to biased and unreliable models, while high-quality data enables accurate predictions and insights. What is Data Quality in Machine Learning? Bias in data can result in unfair and discriminatory outcomes.

Data Quality 52

Data Quality Machine Learning Machine Learning Clean Data 52

DagsHub

AUGUST 23, 2024

As such, the quality of their data can make or break the success of the company. This article will guide you through the concept of a data quality framework, its essential components, and how to implement it effectively within your organization. What is a data quality framework?

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Dataconomy

MAY 16, 2023

Key skills and qualifications for machine learning engineers include: Strong programming skills: Proficiency in programming languages such as Python, R, or Java is essential for implementing machine learning algorithms and building data pipelines.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making. Data Lakes allow for flexible analysis.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

Pickl AI

DECEMBER 16, 2024

This step includes: Identifying Data Sources: Determine where data will be sourced from (e.g., Ensuring Time Consistency: Ensure that the data is organized chronologically, as time order is crucial for time series analysis. Cleaning Data: Address any missing values or outliers that could skew results.

AI 52

AI AI Machine Learning Machine Learning 52