Marktechpost

AUGUST 27, 2024

Data analysis helps organizations make informed decisions by turning raw data into actionable insights. With businesses increasingly relying on data-driven strategies, the demand for skilled data analysts is rising. You’ll learn the fundamentals of gathering, cleaning, analyzing, and visualizing data.

Data Analysis 56

Data Analysis Python Data Scientist Big Data 56

Marktechpost

JUNE 5, 2024

You may use OpenRefine for more than just data cleaning; it can also help you find mistakes and outliers that could compromise your data’s quality. Apache Griffin Apache Griffin is an open-source data quality tool that aims to enhance big data processes.

Data Quality 110

Data Quality Metadata Data Integration ETL 110

Pickl AI

JULY 6, 2023

Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis. It applies the data structure during querying rather than data ingestion. This delay makes Hive less suitable for real-time or interactive data analysis. Why Do We Need Hadoop Hive?

Big Data 52

Big Data Data Analysis ETL Metadata 52

ODSC - Open Data Science

APRIL 3, 2023

We looked at over 25,000 job descriptions, and these are the data analytics platforms, tools, and skills that employers are looking for in 2023. Excel is the second most sought-after tool in our chart as you’ll see below as it’s still an industry standard for data management and analytics.

Data Science 52

Data Science Big Data ETL Deep Learning 52

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 Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Science 52

Data Science Data Scientist ETL Machine Learning 52

Pickl AI

SEPTEMBER 19, 2024

It discusses performance, use cases, and cost, helping you choose the best framework for your big data needs. Introduction Apache Spark and Hadoop are potent frameworks for big data processing and distributed computing. Apache Spark is an open-source, unified analytics engine for large-scale data processing.

Big Data 52

Big Data ETL Machine Learning Python 52

TransOrg Analytics

AUGUST 9, 2024

Data Quality: Without proper governance, data quality can become an issue. Performance: Query performance can be slower compared to optimized data stores. Business Applications: Big Data Analytics : Supporting advanced analytics, machine learning, and artificial intelligence applications.

Machine Learning 52

Machine Learning ETL Big Data Data Quality 52

Pickl AI

OCTOBER 10, 2024

Enhanced Data Quality : These tools ensure data consistency and accuracy, eliminating errors often occurring during manual transformation. Scalability : Whether handling small datasets or processing big data, transformation tools can easily scale to accommodate growing data volumes.

ETL 52

ETL Data Quality Machine Learning Business Intelligence 52

Pickl AI

JANUARY 15, 2025

As businesses increasingly rely on data-driven strategies, the global BI market is projected to reach US$36.35 The rise of big data, along with advancements in technology, has led to a surge in the adoption of BI tools across various sectors. Data Processing: Cleaning and organizing data for analysis.

Business Intelligence 52

Business Intelligence ETL Data Mining Data Analysis 52

Pickl AI

NOVEMBER 15, 2023

Data scientists can explore, experiment, and derive valuable insights without the constraints of a predefined structure. This capability empowers organizations to uncover hidden patterns, trends, and correlations in their data, leading to more informed decision-making. What Is a Data Warehouse?

ETL 52

ETL Metadata Business Intelligence Data Analysis 52

Pickl AI

JANUARY 28, 2025

Data Integration Once data is collected from various sources, it needs to be integrated into a cohesive format. Data Quality Management : Ensures that the integrated data is accurate, consistent, and reliable for analysis. They store structured data in a format that facilitates easy access and analysis.

Business Intelligence 52

Business Intelligence ETL Data Integration Automation 52

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. Explain the Extract, Transform, Load (ETL) process.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

ODSC - Open Data Science

APRIL 4, 2024

Data Analytics in the Age of AI, When to Use RAG, Examples of Data Visualization with D3 and Vega, and ODSC East Selling Out Soon Data Analytics in the Age of AI Let’s explore the multifaceted ways in which AI is revolutionizing data analytics, making it more accessible, efficient, and insightful than ever before.

Data Science 52

Data Science ETL Big Data Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. ETL is vital for ensuring data quality and integrity.

Data Quality 52

Data Quality ETL Data Integration Machine Learning 52

Artificial Corner

JUNE 6, 2023

Timeline of data engineering — Created by the author using canva In this post, I will cover everything from the early days of data storage and relational databases to the emergence of big data, NoSQL databases, and distributed computing frameworks. MongoDB, developed by MongoDB Inc.,

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Marktechpost

JULY 17, 2023

It is a clear leader in all types of analytics tools and methodologies, including predictive analytics, and has continued to invent new tools used by statisticians and data scientists. government launched the first version of the company’s tools to better data analysis for healthcare in 1966.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

Marktechpost

JULY 23, 2023

Big data analytics are supported by scalable, object-oriented services. Each of the “buckets” used to store data has a maximum capacity of 5 terabytes. It’s perfect for deriving real-time business intelligence from extensive data analysis.

Machine Learning 52

Machine Learning Big Data ETL Data Integration 52

Bugra Akyildiz

JUNE 29, 2024

This week, I will cover why I think data janitor work is dying and companies that are built in on top of data janitor work could be ripe for disruption through LLMs and what to do about it. A data janitor is a person who works to take big data and condense it into useful amounts of information.

LLM 40

LLM Big Data Data Quality ETL 40

Pickl AI

JUNE 11, 2024

Let’s delve into the key components that form the backbone of a data warehouse: Source Systems These are the operational databases, CRM systems, and other applications that generate the raw data feeding the data warehouse. Data Extraction, Transformation, and Loading (ETL) This is the workhorse of architecture.

ETL 52

ETL Data Mining Data Integration Actionable Intelligence 52

Pickl AI

MARCH 10, 2025

In this blog, well explore the 5 key components of Power BI , their features, and how they can help you make data-driven decisions. Key Takeaways User-Friendly Interface: Simplifies data analysis for non-technical users. Key Features Data Import: Connects to multiple data sources like Excel, SQL Server, or cloud services.

Business Intelligence 52

Business Intelligence ETL Data Analysis Natural Language Processing 52

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. Users can write data to managed RMS tables using Iceberg APIs, Amazon Redshift, or Zero-ETL ingestion from supported data sources.

Metadata 132

Metadata ETL Data Analysis Big Data 132

Marktechpost

NOVEMBER 23, 2024

Data analysis helps organizations make informed decisions by turning raw data into actionable insights. With businesses increasingly relying on data-driven strategies, the demand for skilled data analysts is rising. You’ll learn the fundamentals of gathering, cleaning, analyzing, and visualizing data.

Data Analysis 111

Data Analysis Python Data Scientist Big Data 111

AWS Machine Learning Blog

NOVEMBER 12, 2024

Current challenges in analyzing field trial data Agronomic field trials are complex and create vast amounts of data. Most companies are unable to use their field trial data based on manual processes and disparate systems. The first step in developing and deploying generative AI use cases is having a well-defined data strategy.

Generative AI 112

Generative AI Prompt Engineering Prompt Engineer AI 112