Pickl AI

MARCH 4, 2024

With its intuitive interface, Power BI empowers users to connect to various data sources, create interactive reports, and share insights effortlessly. Optimising Power BI reports for performance ensures efficient data analysis. What is Power BI, and how does it differ from other data visualisation tools?

Power BI 52

Power BI Data Analysis Data Analysis Data Models 52

Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Orchestration.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Orchestration.

Tableau 98

Tableau Data Quality Analytics Analytics 98

Pickl AI

OCTOBER 17, 2023

Learn how Data Scientists use ChatGPT, a potent OpenAI language model, to improve their operations. ChatGPT is essential in the domains of natural language processing, modeling, data analysis, data cleaning, and data visualization. It facilitates exploratory Data Analysis and provides quick insights.

Data Scientist 52

Data Scientist Machine Learning Machine Learning Data Science 52

Pickl AI

APRIL 10, 2023

Data Analysis is one of the most crucial tasks for business organisations today. SQL or Structured Query Language has a significant role to play in conducting practical Data Analysis. Data Analysts need deeper knowledge on SQL to understand relational databases like Oracle, Microsoft SQL and MySQL.

Data Analyst 52

Data Analyst SQL Data Analysis Data Analysis 52

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

OCTOBER 10, 2024

Summary: This blog presents 15 advanced Excel interview questions designed to evaluate candidates’ expertise in data analysis, formula usage, and spreadsheet management. Topics include VLOOKUP vs. INDEX/MATCH, pivot tables, macros, and data validation. What are array formulas, and how do you use them?

Data Analysis 52

Data Analysis Data Analysis Data Modeling Data Models 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.

Power BI 52

Power BI Tableau Data Analysis Data Analysis 52

Tableau

SEPTEMBER 23, 2021

The right tooling will help you put your governance framework into practice, providing the necessary guardrails and data visibility that your teams need to boost trust and confidence in their data analysis. . Data modeling. Data migration . Data architecture. Metadata management.

Data Governance 102

Data Governance Analytics Analytics Tableau 102

Tableau

SEPTEMBER 23, 2021

The right tooling will help you put your governance framework into practice, providing the necessary guardrails and data visibility that your teams need to boost trust and confidence in their data analysis. . Data modeling. Data migration . Data architecture. Metadata management.

Data Governance 97

Data Governance Analytics Analytics Tableau 97

Pickl AI

JUNE 23, 2023

Data Collection The process begins with the collection of relevant and diverse data from various sources. This can include structured data (e.g., databases, spreadsheets) as well as unstructured data (e.g., Data Preparation Once collected, the data needs to be preprocessed and prepared for analysis.

AI 52

AI AI Data Governance Data Quality 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

Iguazio

DECEMBER 14, 2023

There are 6 high-level steps in every MLOps project The 6 steps are: Initial data gathering (for exploration). Exploratory data analysis (EDA) and modeling. Data and model pipeline development (data preparation, training, evaluation, and so on). Deploy according to various strategies.

ML 52

ML ML Data Science Data Preparation 52

Pickl AI

NOVEMBER 28, 2024

Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data. Model evaluation and tuning involve several techniques to assess and optimise model accuracy and reliability.

Machine Learning 52

Machine Learning Machine Learning ML ML 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

DagsHub

APRIL 21, 2024

You need to make that model available to the end users, monitor it, and retrain it for better performance if needed. Similar to TensorFlow, PyTorch is also an open-source tool that allows you to develop deep learning models for free.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

The MLOps Blog

MAY 9, 2023

A typical machine learning pipeline with various stages highlighted | Source: Author Common types of machine learning pipelines In line with the stages of the ML workflow (data, model, and production), an ML pipeline comprises three different pipelines that solve different workflow stages. They include: 1 Data (or input) pipeline.

ML 98

ML ML Machine Learning Machine Learning 98