Towards AI

JANUARY 27, 2023

In the increasingly competitive world, understanding the data and taking quicker actions based on that help create differentiation for the organization to stay ahead! It is used to discover trends [2], patterns, relationships, and anomalies in data, and can help inform the development of more complex models [3].

Exploratory Data Analysis 94

Exploratory Data Analysis Data Analysis Data Analysis EDA 94

IBM Journey to AI blog

MAY 17, 2024

Without knowing what to look for, business analysts can miss critical insights, making dashboards less effective for exploratory data analysis and real-time decision-making. With simpler interfaces that include conversational interfaces, these tools make interacting with data as easy as having a chat.

Exploratory Data Analysis 101

Exploratory Data Analysis Data Analysis Data Analysis Business Intelligence 101

Pickl AI

APRIL 26, 2024

Top 50+ Interview Questions for Data Analysts Technical Questions SQL Queries What is SQL, and why is it necessary for data analysis? SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. How would you segment customers based on their purchasing behaviour?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

NOVEMBER 15, 2023

This empowers decision-makers at all levels to gain a comprehensive understanding of business performance, trends, and key metrics, fostering data-driven decision-making. Historical Data Analysis Data Warehouses excel in storing historical data, enabling organizations to analyze trends and patterns over time.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

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 Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 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. For example, where verified data is present, the latencies are quantified.

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. For example, where verified data is present, the latencies are quantified.

Machine Learning 52

Machine Learning Machine Learning ML ML 52