Data Science Dojo

MAY 18, 2023

Data Storytelling in Action: This panel will discuss the importance of data visualization in storytelling in different industries, different visualization tools, tips on improving one’s visualization skills, personal experiences, breakthroughs, pressures, and frustrations as well as successes and failures.

Data Science 195

Data Science AI AI SQL 195

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Read more to know.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Data Science Blog

NOVEMBER 15, 2023

The lower part of the iceberg is barely visible to the normal analyst on the tool interface, but is essential for implementation and success: this is the Event Log as the data basis for graph and data analysis in Process Mining. The creation of this data model requires the data connection to the source system (e.g.

Data Models 245

Data Models Data Modeling Business Intelligence Business Intelligence 245

Dataconomy

JULY 28, 2023

Proper data preprocessing is essential as it greatly impacts the model performance and the overall success of data analysis tasks ( Image Credit ) Data integration Data integration involves combining data from various sources and formats into a unified and consistent dataset.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Data Science Dojo

JULY 3, 2024

Here’s a list of key skills that are typically covered in a good data science bootcamp: Programming Languages : Python : Widely used for its simplicity and extensive libraries for data analysis and machine learning. R : Often used for statistical analysis and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

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

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.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

phData

MARCH 27, 2024

The exam will cover all aspects of using Snowflake and its components to apply data analysis principles, from preparing and loading data to presenting data and meeting business requirements. I found the Data Engineering Simplified’s playlists particularly beneficial during my studies.

Data Analyst 52

Data Analyst Data Engineering Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 5, 2024

Data Preparation: Cleaning, transforming, and preparing data for analysis and modelling. Collaborating with Teams: Working with data engineers, analysts, and stakeholders to ensure data solutions meet business needs. Other valuable certifications include Microsoft Certified: Azure AI Engineer Associate.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Mlearning.ai

JULY 11, 2023

For instance, feature engineering and exploratory data analysis (EDA) often require the use of visualization libraries like Matplotlib and Seaborn. Moreover, tools like Power BI and Tableau can produce remarkable results. In the data science industry, effective communication and collaboration play a crucial role.

Data Science 40

Data Science Exploratory Data Analysis Azure Power BI 40

Pickl AI

SEPTEMBER 12, 2023

Career Progression As you gain experience and expertise in Data Science, you have the opportunity for career progression. Roles such as Data Scientist, Machine Learning Engineer, Data Analyst, and Data Engineer offer clear pathways for growth and specialization. Python, R).

Data Science 52

Data Science Data Analyst Machine Learning Machine Learning 52

Pickl AI

JUNE 4, 2024

Big Data Analytics This involves analyzing massive datasets that are too large and complex for traditional data analysis methods. Big Data Analytics is used in healthcare to improve operational efficiency, identify fraud, and conduct large-scale population health studies.

Data Science 52

Data Science Big Data Analytics Big Data Analytics Predictive Analytics 52

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. Thats where data engineering tools come in!

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52