Marktechpost

NOVEMBER 19, 2024

With their own unique architecture, capabilities, and optimum use cases, data warehouses and big data systems are two popular solutions. The differences between data warehouses and big data have been discussed in this article, along with their functions, areas of strength, and considerations for businesses.

Big Data 80

Big Data ETL Business Intelligence Data Analysis 80

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 ETL Data Scientist 56

Unite.AI

SEPTEMBER 24, 2024

This article explores some of the most innovative AI-driven supply chain platforms that are revolutionizing how companies plan, execute, and analyze their operations. Additionally, the platform utilizes natural language processing (NLP) to enable real-time insights and decision-making, enhancing supply chain visibility and agility.

AI Tools 162

AI Tools Natural Language Processing Machine Learning Artificial Intelligence 162

Pickl AI

APRIL 26, 2024

This article aims to guide you through the intricacies of Data Analyst interviews, offering valuable insights with a comprehensive list of top questions. Additionally, we’ve got your back if you consider enrolling in the best data analytics courses. Case Study Questions Imagine you have a dataset of customer transactions.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Pickl AI

OCTOBER 16, 2024

Summary: Relational Database Management Systems (RDBMS) are the backbone of structured data management, organising information in tables and ensuring data integrity. Introduction RDBMS is the foundation for structured data management. These rules prevent duplicate records and maintain referential integrity.

Data Integration 52

Data Integration Big Data Machine Learning Business Intelligence 52

Pickl AI

AUGUST 5, 2024

These functions enhance Data Analysis, reporting, and decision-making. It plays a crucial role in Data Analysis and retrieval. SQL aggregate functions, such as COUNT(), SUM(), AVG(), MIN(), and MAX(), are essential for performing calculations on data sets. Read: Introduction to MySQL.

Data Analysis 52

Data Analysis Data Integration 52

Pickl AI

JUNE 16, 2024

Summary: Excel’s COUNT function efficiently tallies numeric entries, enhancing Data Analysis accuracy. Additionally, counting characters using formulas like LEN aids in text analysis. Mastering these count formulas in Excel is crucial for precise data management and boosting productivity in data-driven tasks.

Data Analysis 52

Data Analysis Data Quality Data Integration Automation 52

Pickl AI

NOVEMBER 18, 2024

Summary: Power BI alternatives like Tableau, Qlik Sense, and Zoho Analytics provide businesses with tailored Data Analysis and Visualisation solutions. Selecting the right alternative ensures efficient data-driven decision-making and aligns with your organisation’s goals and budget. billion to USD 54.27

Data Analysis 52

Data Analysis Business Intelligence Big Data Artificial Intelligence 52

Pickl AI

JULY 25, 2023

Two prominent roles that play a crucial part in this data-driven landscape are Data Scientists and Data Engineers. At the core of Data Science lies the art of transforming raw data into actionable information that can guide strategic decisions. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Science 52

Data Science Data Scientist ETL Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

The global Big Data and Data Engineering Services market, valued at USD 51,761.6 This article explores the key fundamentals of Data Engineering, highlighting its significance and providing a roadmap for professionals seeking to excel in this vital field. Data modelling is crucial for structuring data effectively.

Data Quality 52

Data Quality ETL Data Integration Machine Learning 52

Marktechpost

JULY 17, 2023

Algorithms and models Predictive analytics uses several methods from fields like machine learning, data mining, statistics, analysis, and modeling. In this article, some of them are described. 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

Pickl AI

NOVEMBER 3, 2024

Summary: Pattern matching in SQL enables users to identify specific sequences of data within databases using various techniques such as the LIKE operator and regular expressions. This powerful feature enhances data analysis, allowing for complex queries that can uncover trends and insights across datasets.

Data Analysis 52

Data Analysis Data Integration Data Science Artificial Intelligence 52

Pickl AI

OCTOBER 10, 2024

Data transformation tools simplify this process by automating data manipulation, making it more efficient and reducing errors. These tools enable seamless data integration across multiple sources, streamlining data workflows.

ETL 52

ETL Data Quality Business Intelligence Machine Learning 52

Pickl AI

NOVEMBER 14, 2023

Your journey ends here where you will learn the essential handy tips quickly and efficiently with proper explanations which will make any type of data importing journey into the Python platform super easy. Introduction Are you a Python enthusiast looking to import data into your code with ease?

Python 52

Python Data Analysis Data Science Data Scientist 52

Pickl AI

JANUARY 10, 2025

Summary: The article highlights how AI will impact the data backup industry. It analyses the functions of artificial intelligence and machine learning and how they can affect the data backup process. Introduction Do you want to know if AI can improve data backup strategies and influence the backup industry?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Automation AI 52

Heartbeat

OCTOBER 25, 2023

With its ability to analyze and interpret vast amounts of complex biological data, bioinformatics has emerged as a critical discipline in the “Age of Bioinformatics.” Integrating and analyzing data from multiple platforms and experiments pose challenges due to data formats, normalization techniques, and data quality differences.

Machine Learning 52

Machine Learning Data Scientist Convolutional Neural Networks Algorithm 52

Pickl AI

OCTOBER 18, 2023

Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends. However, the mere accumulation of data is not enough; ensuring data quality is paramount. Informed Decision-making High-quality data empowers organizations to make informed decisions with confidence.

Data Quality 52

Data Quality ML Machine Learning Natural Language Processing 52

Pickl AI

JULY 12, 2023

We are living in a world where data drives decisions. Data manipulation in Data Science is the fundamental process in data analysis. The data professionals deploy different techniques and operations to derive valuable information from the raw and unstructured data.

Data Analysis 52

Data Analysis Data Science Data Quality Python 52

Heartbeat

OCTOBER 23, 2023

Revolutionizing Healthcare through Data Science and Machine Learning Image by Cai Fang on Unsplash Introduction In the digital transformation era, healthcare is experiencing a paradigm shift driven by integrating data science, machine learning, and information technology.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

Pickl AI

JUNE 7, 2024

Encapsulation safeguards data integrity by restricting direct access to an object’s data and methods. Introduction This article explores the fascinating concepts of abstraction and encapsulation in Python. Have you ever wondered why encapsulation is crucial for protecting data in Python?

Python 40

Python Explainability Software Development Data Integration 40

Pickl AI

OCTOBER 23, 2024

Summary: This article delves into the importance of sample size in statistical analyses, highlighting its impact on tests such as t-tests, ANOVA, regression, and Chi-Square tests. This ensures that conclusions drawn from the analysis are valid, enabling researchers to make informed predictions and decisions based on data.

Categorization 52

Categorization Data Analysis Data Integration 52

Mlearning.ai

AUGUST 10, 2023

The article will be presented in 5 sections, which will be described as follows: Section 1: Brief description that acts as the motivating foundation of this research. It is a data integration process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target system.

Business Intelligence 52

Business Intelligence ETL Data Analysis Python 52

Pickl AI

SEPTEMBER 12, 2024

Whether you’re a business analysing customer behaviour or a researcher conducting a study, the right example of data collection ensures reliable outcomes. Data collection is important because it can provide actionable insights. What Is Data Collection? Use Reliable Tools : Choose reliable tools and software that meet your needs.

Data Analysis 52

Data Analysis Data Quality Machine Learning Data Integration 52

ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. 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.

ETL 52

ETL Business Intelligence Data Science Data Analysis 52

Pickl AI

JUNE 23, 2023

And to effectively harness the power of data, organizations are adopting data-centric architectures in AI. But what exactly is data-centric architecture in AI? In this article, we will delve deep into this topic, exploring its significance, benefits, and implementation strategies. So, let’s get started!

Continuous Learning 52

Continuous Learning Data Quality AI AI 52

Pickl AI

NOVEMBER 27, 2024

Integrating both into Data Science workflows enhances flexibility, expands access to diverse libraries, and improves performance by leveraging the best features of each language. Python for Data Science Python has become the go-to programming language for Data Science due to its simplicity, versatility, and powerful libraries.

Data Science 52

Data Science Python Machine Learning Data Scientist 52

Pickl AI

JULY 18, 2023

Programming for Data Science enables Data Scientists to analyze vast amounts of data and extract meaningful information. There are different programming languages and in this article, we will explore 8 programming languages that play a crucial role in the realm of Data Science. Wrapping it up !!!

Data Science 52

Data Science Data Scientist Python Business Intelligence 52

Pickl AI

SEPTEMBER 5, 2024

Introduction Managing duplicates in Excel is crucial for ensuring data accuracy and enhancing analysis. This article will guide you through how to find duplicates in Excel, highlight duplicates in Excel, and remove duplicates in Excel. Recognising and addressing these duplicates is crucial for maintaining data integrity.

Data Integration 52

Data Integration Automation Data Analysis Data Quality 52

Bugra Akyildiz

JUNE 29, 2024

Data Normalization : Scaling and transforming data to a common range or distribution to ensure compatibility across different data sources and models. Data Deduplication : Identifying and removing duplicate records or entries to maintain data integrity and consistency.

LLM 40

LLM Big Data Data Quality ETL 40

Pickl AI

NOVEMBER 5, 2024

Summary: Data Visualisation is crucial to ensure effective representation of insights tableau vs power bi are two popular tools for this. This article compares Tableau and Power BI, examining their features, pricing, and suitability for different organisations. billion in 2023. It is expected to grow to USD 31.98

Business Intelligence 52

Business Intelligence Data Analysis Data Extraction Big Data 52

Pickl AI

OCTOBER 9, 2024

Introduction Clustering in data mining is a pivotal technique that enables the grouping of similar data points into clusters, facilitating better Data Analysis and interpretation. This process helps uncover hidden patterns and relationships in the data that might not be immediately apparent.

Data Mining 52

Data Mining Algorithm Categorization Data Analysis 52

Pickl AI

SEPTEMBER 25, 2024

Introduction Python sets are powerful data structures that store unique elements, making them ideal for handling collections without duplicates. They are widely used in Data Analysis , filtering, and database operations where uniqueness is crucial. union(set2, set3).

Python 52

Python Data Analysis Data Science Data Integration 52

Pickl AI

DECEMBER 9, 2024

Summary: This article provides a comprehensive guide on Big Data interview questions, covering beginner to advanced topics. Introduction Big Data continues transforming industries, making it a vital asset in 2025. The global Big Data Analytics market, valued at $307.51 billion in 2023, is projected to grow to $348.21

Big Data 52

Big Data Explainability Metadata Data Quality 52

Viso.ai

NOVEMBER 11, 2024

In this article, we’ll delve into AI in AUVs. The data from these devices can then be turned into maps, AI techniques can be used to enhance the map and accelerate its creation in several ways. Occupancy Grids Depth Estimation Oceanographic Data Integration Underwater maps generated by sonar and sensor data.

Computer Vision 52

Computer Vision Neural Network Algorithm AI 52

Artificial Corner

JUNE 6, 2023

This made them ideal for trend analysis, business reporting, and decision support. The development of data warehouses marked a shift in how businesses used data, moving from transactional processing to data analysis and decision support. MapReduce: simplified data processing on large clusters.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

Heartbeat

MAY 29, 2023

A small portion of the LLM ecosystem; image from scalevp.com In this article, we will provide a comprehensive guide to training, deploying, and improving LLMs. In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning.

Large Language Models 78

Large Language Models Machine Learning LLM Natural Language Processing 78

Marktechpost

NOVEMBER 4, 2024

Professionals known as data analysts enable this by turning complicated raw data into understandable, useful insights that help in decision-making. They navigate the whole data analysis cycle, from discovering and collecting pertinent data to getting it ready for analysis, interpreting the findings, and formulating suggestions.

Data Analysis 81

Data Analysis Machine Learning Data Science Python 81