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 What is Big Data?

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Pickl AI

JANUARY 12, 2025

Introduction Are you struggling to decide between data-driven practices and AI-driven strategies for your business? Besides, there is a balance between the precision of traditional data analysis and the innovative potential of explainable artificial intelligence.

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Becoming Human

JANUARY 23, 2023

- a beginner question Let’s start with the basic thing if I talk about the formal definition of Data Science so it’s like “Data science encompasses preparing data for analysis, including cleansing, aggregating, and manipulating the data to perform advanced data analysis” , is the definition enough explanation of data science?

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Unite.AI

MARCH 6, 2025

and get a quick analysis. Alma can also assist newbies by explaining terms or suggesting next steps in the investing process. Beyond Q&A, Alma can analyze property data on the fly, compute ROI or rental estimates, and even draft outreach messages. or What are some potential exit strategies for this property?

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Flipboard

DECEMBER 11, 2024

SageMaker Unied Studio is an integrated development environment (IDE) for data, analytics, and AI. Discover your data and put it to work using familiar AWS tools to complete end-to-end development workflows, including data analysis, data processing, model training, generative AI app building, and more, in a single governed environment.

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AWS Machine Learning Blog

MARCH 18, 2025

LLM-powered data analysis The transcribed interviews and ingested documents are fed into a powerful LLM, which can understand and correlate the information from multiple sources. The LLM can identify key insights, potential issues, and areas of non-compliance by analyzing the content and context of the data.

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Unite.AI

JULY 26, 2023

Given that persona, explain the key events and reasons leading to the downfall of the French monarchy.” For instance, a user might be interested in the potential impact of artificial intelligence on job markets: User : “Could you briefly explain the concept of artificial intelligence?”

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Unite.AI

OCTOBER 7, 2024

Gathering more data on the effectiveness of treatments will ultimately improve the quality of care based on big data analysis. Could you explain the role of the 3D camera system in enhancing the effectiveness of the treatments? You can think of massage lines as tracks that are mapped onto the patient's body.

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AWS Machine Learning Blog

APRIL 7, 2025

This not only speeds up content production but also allows human writers to focus on more creative and strategic tasks. - **Data Analysis and Summarization**: These models can quickly analyze large volumes of data, extract relevant information, and summarize findings in a readable format.

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Pickl AI

JULY 23, 2023

While unstructured data may seem chaotic, advancements in artificial intelligence and machine learning enable us to extract valuable insights from this data type. Big Data Big data refers to vast volumes of information that exceed the processing capabilities of traditional databases.

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Pickl AI

JANUARY 13, 2025

Explains search algorithms and game theory. Using simple language, it explains how to perform data analysis and pattern recognition with Python and R. Explains real-world applications like fraud detection. It explains reinforcement, supervised, and unsupervised learning with case studies and examples.

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Pickl AI

OCTOBER 9, 2023

Unlike supervised learning, where the algorithm is trained on labeled data, unsupervised learning allows algorithms to autonomously identify hidden structures and relationships within data. These algorithms can identify natural clusters or associations within the data, providing valuable insights for demand forecasting.

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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 difference between a bar chart and a histogram.

Data Analysis 52

Data Analysis Machine Learning ETL Explainability 52

Pickl AI

DECEMBER 10, 2024

Look for books that explain technical jargon in plain language and use analogies to simplify abstract ideas. Coverage of Foundational Topics A strong foundation is critical in Data Science. Ensure the book covers essential topics such as statistics, basic programming ( Python or R ), and data visualisation.

Data Science 52

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Pickl AI

SEPTEMBER 4, 2023

Data Visualization: Create clear and informative data visualisations, such as graphs and charts, to communicate findings to non-technical stakeholders. Statistical Software and Tools: Use statistical software like R, Python, SAS, or specialised tools to conduct data analysis and generate reports.

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Pickl AI

JULY 10, 2023

As a programming language it provides objects, operators and functions allowing you to explore, model and visualise data. The programming language can handle Big Data and perform effective data analysis and statistical modelling.

Data Science 52

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Flipboard

MARCH 22, 2023

Data Wrangler makes it easy to ingest data and perform data preparation tasks such as exploratory data analysis, feature selection, and feature engineering. His knowledge ranges from application architecture to big data, analytics, and machine learning. Bosco Albuquerque is a Sr.

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Pragnakalp

APRIL 29, 2024

Step 3: Load and process the PDF data For this blog, we will use a PDF file to perform the QnA on it. We’ve selected a research paper titled “DEEP LEARNING APPLICATIONS AND CHALLENGES IN BIG DATA ANALYTICS,” which can be accessed at the following link: [link] Please download the PDF and place it in your working directory.

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Pickl AI

SEPTEMBER 5, 2024

Unified Data Services: Azure Synapse Analytics combines big data and data warehousing, offering a unified analytics experience. Azure’s global network of data centres ensures high availability and performance, making it a powerful platform for Data Scientists to leverage for diverse data-driven projects.

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Heartbeat

OCTOBER 25, 2023

The field demands a unique combination of computational skills and biological knowledge, making it a perfect match for individuals with a data science and machine learning background. Developing methods for model interpretability and explainability is an active area of research in bioinformatics.

Machine Learning 52

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ODSC - Open Data Science

FEBRUARY 6, 2024

LLMs Meet Google Cloud: A New Frontier in Big Data Analytics Mohammad Soltanieh-ha, PhD | Clinical Assistant Professor | Boston University Dive into the world of cloud computing and big data analytics with Google Cloud’s advanced tools and big data capabilities.

Large Language Models 52

Large Language Models Big Data LLM Data Science 52

Pickl AI

MAY 29, 2024

Mastering programming, statistics, Machine Learning, and communication is vital for Data Scientists. A typical Data Science syllabus covers mathematics, programming, Machine Learning, data mining, big data technologies, and visualisation. What does a typical Data Science syllabus cover?

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ODSC - Open Data Science

OCTOBER 20, 2023

The Tangent Information Modeler, Time Series Modeling Reinvented Philip Wauters | Customer Success Manager and Value Engineer | Tangent Works Existing techniques for modeling time series data face limitations in scalability, agility, explainability, and accuracy. Check them out for free!

Data Science 52

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Marktechpost

JULY 17, 2023

The company’s H20 Driverless AI streamlines AI development and predictive analytics for professionals and citizen data scientists through open source and customized recipes. When necessary, the platform also enables numerous governance and explainability elements.

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Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

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Pickl AI

OCTOBER 15, 2024

Diagnostic Analytics Diagnostic analytics goes a step further by explaining why certain events occurred. It uses data mining , correlations, and statistical analyses to investigate the causes behind past outcomes. Organisations that harness Big Data can gain comprehensive insights into customer preferences and market trends.

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ODSC - Open Data Science

AUGUST 21, 2023

You will also get invaluable insights by networking and connecting with hundreds of data science attendees, world-renowned instructors, industry experts, and dozens of top companies seeking the next wave of talent. You’ll also hear use cases on how data can be used to optimize business performance.

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Pickl AI

JUNE 12, 2023

A Data Scientist requires to be able to visualize quickly the data before creating the model and Tableau is helpful for that. With SQL queries Tableau helps in integrating with them effectively. Disadvantages of Tableau for Data Science However, apart from the advantages, Tableau for Data Science also has its own disadvantages.

Data Science 52

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Pickl AI

FEBRUARY 12, 2024

Communication skills Articulating complex ideas, explaining methodologies, and presenting findings in a clear and concise manner are essential components of Data Science roles. The choice of method depends on the nature of the data and the specific requirements of the analysis.

Data Science 52

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Dlabs.ai

NOVEMBER 24, 2020

We’ve written in-depth about the differences between AI, Machine Learning, Big Data, and Data Science. Today, it’s time to explore another term that holds equal weight in the modern business world: Data Mining. Step 2: Data Cleaning When you collect lots of data, you inevitably collate unnecessary information.

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Pickl AI

FEBRUARY 19, 2025

Big Data: Refers to vast sets of data that traditional tools cannot process; commonly used in industries like social media, e-commerce, and healthcare. Data Visualisation: Presents data in visual formats, such as graphs and charts; helps identify patterns and trends for better decision-making.

Data Science 52

Data Science Machine Learning Data Scientist Algorithm 52

Pickl AI

NOVEMBER 28, 2024

Knowledge of Cloud Computing and Big Data Tools As complex Machine Learning (ML) models grow, robust infrastructure for large datasets and intensive computations becomes increasingly important. Big Data Tools Integration Big data tools like Apache Spark and Hadoop are vital for managing and processing massive datasets.

Machine Learning 52

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Mlearning.ai

JANUARY 26, 2023

ARCO and 4C’s For state-of-the-art data cubes it is important to emphasize the following term “ARCO” = Analysis-Ready Cloud Optimized ( Stern et al., The meaning of this term is explained below. For example, vector maps of roads of an area coming from different sources is the raw data.

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Dlabs.ai

MAY 22, 2022

The instructors are very good at explaining complex topics in an easy-to-understand way. What is data analysis? How to train data to obtain valuable insights The artificial intelligence course itself is free. However, the exam and the certificate cost $99 — but it is from Harvard, so it’s worth it, right?

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ODSC - Open Data Science

MARCH 11, 2024

You will also get invaluable insights by networking and connecting with hundreds of data science attendees, world-renowned instructors, industry experts, and dozens of top companies seeking the next wave of talent. You’ll also hear use cases on how data can be used to optimize business performance.

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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. The platform’s schema independence allows you to directly consume data in any format or type.

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