Pickl AI

JUNE 18, 2024

Summary: This blog dives into the most promising Power BI projects, exploring advanced data visualization, AI integration, IoT & blockchain analytics, and emerging technologies. Discover best practices for successful implementation and propel your organization towards data-driven success.

Power BI 52

Power BI Data Analysis Data Analysis Data Visualization 52

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Key Components of Data Intelligence In Data Intelligence, understanding its core components is like deciphering the secret language of information.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

Women in Big Data

DECEMBER 9, 2024

Its strength lies in its ability to handle efficient big data processing and perform complex data analysis with ease. With features like calculated fields, trend lines, and statistical summaries, Tableau empowers users to conduct in-depth analysis and derive actionable insights from their data.

Big Data 52

Big Data Big Data Power BI Tableau 52

Pickl AI

JUNE 23, 2023

Continuous Learning and Iteration Data-centric AI systems often incorporate mechanisms for continuous learning and adaptation. As new data becomes available, the models can be retrained or fine-tuned to improve their performance over time. Evaluates the performance of AI systems based on model accuracy and performance metrics.

AI 52

AI AI Data Governance Data Quality 52

Pickl AI

JULY 3, 2023

It is the process of converting raw data into relevant and practical knowledge to help evaluate the performance of businesses, discover trends, and make well-informed choices. Data gathering, data integration, data modelling, analysis of information, and data visualization are all part of intelligence for businesses.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

ODSC - Open Data Science

JUNE 12, 2023

This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling. in an enterprise data warehouse. What is a Datamart? A replacement for datasets.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

phData

APRIL 20, 2023

Variant columns can be used to store data that doesn’t fit neatly into traditional columns, such as nested data structures, arrays, or key-value pairs. Using variant columns in data vault satellites in Snowflake can provide several benefits. Again dbt Data Vault package automates a major portion of it.

Data Warehouse 72

Data Warehouse Data Governance Clustering Database 72

Pickl AI

JULY 25, 2023

At the core of Data Science lies the art of transforming raw data into actionable information that can guide strategic decisions. Role of Data Scientists Data Scientists are the architects of data analysis. They clean and preprocess the data to remove inconsistencies and ensure its quality.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Alation

FEBRUARY 13, 2020

Modern data catalogs—originated to help data analysts find and evaluate data—continue to meet the needs of analysts, but they have expanded their reach. They are now central to data stewardship, data curation, and data governance—all metadata dependent activities. But data catalogs do much more.

Data Lakes 52

Data Lakes Data Governance Data Science Data Analyst 52

The Data Administration Newsletter

JANUARY 17, 2024

Eric Siegel’s “The AI Playbook” serves as a crucial guide, offering important insights for data professionals and their internal customers on effectively leveraging AI within business operations.

AI 122

AI AI Data Quality Data Governance 122

Pickl AI

JUNE 11, 2024

Self-Service Analytics User-friendly interfaces and self-service analytics tools empower business users to explore data independently without relying on IT departments. Best Practices for Maximizing Data Warehouse Functionality A data warehouse, brimming with historical data, holds immense potential for unlocking valuable insights.

Data Warehouse 52

Data Warehouse ETL Data Mining Data Mining 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

phData

SEPTEMBER 1, 2023

This integration ability is particularly important because it allows companies to avoid the costly and time-consuming process of replacing everything in their current data lifecycle. By combining data from disparate systems, HCLS companies can perform better data analysis and make more informed decisions.

Analytics 52

Analytics Analytics Data Analysis Data Analysis 52

Precisely

MARCH 7, 2024

Many people use the term to describe a data quality metric. Technical users, including database administrators, might tell you that data integrity concerns whether or not the data conforms to a pre-defined data model. That gives decision-makers visibility to the “whole truth” of their enterprise data.

Data Quality 52

Data Quality Database Administration Analytics Analytics 52

phData

JULY 10, 2024

Utilize reusable datasets to maintain data consistency and streamline analyses across projects in Sigma. Understanding and utilizing these approaches allows you to effectively leverage custom SQL and CSVs in Sigma Computing to meet your specific data analysis needs. Choose your desired data source type (e.g.,

SQL 52

SQL Data Warehouse Analytics Analytics 52

Pickl AI

OCTOBER 3, 2024

Natural Language Processing (NLP) : Tools for text classification, sentiment analysis, and language translation. Predictive Analytics : Models that forecast future events based on historical data. Continuous Improvement AIMaaS platforms often include tools for monitoring model performance and making adjustments as necessary.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Snorkel AI

MAY 12, 2023

Our data teams focus on three important processes. First, data standardization, then providing model-ready data for data scientists, and then ensuring there’s strong data governance and monitoring solutions and tools in place. Model-ready data refers to a feature library.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Snorkel AI

MAY 12, 2023

Our data teams focus on three important processes. First, data standardization, then providing model-ready data for data scientists, and then ensuring there’s strong data governance and monitoring solutions and tools in place. Model-ready data refers to a feature library.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

OCTOBER 23, 2024

NoSQL Databases NoSQL databases do not follow the traditional relational database structure, which makes them ideal for storing unstructured data. They allow flexible data models such as document, key-value, and wide-column formats, which are well-suited for large-scale data management.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52