Dataconomy

JULY 24, 2023

” Data management and manipulation Data scientists often deal with vast amounts of data, so it’s crucial to understand databases, data architecture, and query languages like SQL. Tools like Tableau, Matplotlib, Seaborn, or Power BI can be incredibly helpful. Machine learning Machine learning is a key part of data science.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Mlearning.ai

MARCH 15, 2023

Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data. Experience with visualization tools like; Tableau and Power BI. Knowledge of big data platforms like; Hadoop and Apache Spark. High proficiency in visualization tools like; Tableau, Google Studio, and Power BI.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

Alation

FEBRUARY 20, 2020

Alation catalogs and crawls all of your data assets, whether it is in a traditional relational data set (MySQL, Oracle, etc), a SQL on Hadoop system (Presto, SparkSQL,etc), a BI visualization or something in a file system, such as HDFS or AWS S3. With Alation, you can search for assets across the entire data pipeline.

SQL 52

SQL Hadoop Analytics Data Pipeline 52

DataSeries

AUGUST 15, 2024

Hadoop, Spark). Practice coding with the help of languages that are used in data engineering like Python, SQL, Scala, or Java. Familiarize with data visualization techniques and tools like Matplotlib, Seaborn, Tableau, or Power BI. Understanding these fundamentals is essential for effective problem-solving in data engineering.

Data Engineering 40

Data Engineering Data Engineer Data Engineering Data Engineering 40

Pickl AI

MAY 29, 2024

Programming Languages (Python, R, SQL) Proficiency in programming languages is crucial. SQL is indispensable for database management and querying. Proficiency with tools like Tableau , Matplotlib , and ggplot2 helps create charts, graphs, and dashboards that effectively communicate insights to stakeholders.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

phData

FEBRUARY 5, 2024

The tool converts the templated configuration into a set of SQL commands that are executed against the target Snowflake environment. Instead of manually converting these queries, consider using software built to automate the translation of queries from your legacy systems language to Snowflake’s version, such as phData’s SQL Translation Tool.

SQL 52

SQL Database Data Quality Data Warehouse 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 98

Data Science Analytics Analytics Data Scientist 98

Pickl AI

FEBRUARY 28, 2023

Effectively, Data Analysts use other tools like SQL, R or Python, Excel, etc., At length, use Hadoop, Spark, and tools like Pig and Hive to develop big data infrastructures. Accordingly, they work with different data types, including sales figures, customer data, financial records and market research data.

Data Analyst 52

Data Analyst Data Scientist Data Science Computer Science 52

ODSC - Open Data Science

APRIL 26, 2023

Because they are the most likely to communicate data insights, they’ll also need to know SQL, and visualization tools such as Power BI and Tableau as well. Some of the tools and techniques unique to business analysts are pivot tables, financial modeling in Excel, Power BI Dashboards for forecasting, and Tableau for similar purposes.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

Smart Data Collective

MAY 20, 2019

For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. SQL programming skills, specific tool experience — Tableau for example — and problem-solving are just a handful of examples. Data processing is another skill vital to staying relevant in the analytics field.

Analytics 111

Analytics Analytics Data Analyst Machine Learning 111

Analytics Vidhya

JUNE 27, 2020

Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20. The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya.

Machine Learning 400

Machine Learning Machine Learning Data Science Analytics 400

Pickl AI

JULY 24, 2023

Skills Required for Data Science To excel in the field of data science, several key skills are essential: Proficiency in programming languages such as Python, R, or SQL Strong statistical knowledge and understanding of mathematical concepts Data manipulation and visualization skills using tools like Pandas, NumPy, and Tableau Machine learning algorithms (..)

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Alation

JANUARY 25, 2022

Alation partners such as Dataiku, Trifacta, and Tableau are perfect examples. For instance, technical power users can explore the actual data through Compose , the intelligent SQL editor. Those less familiar with SQL can search for technical terms using natural language. And this capability will be built out further with time.

DataOps 52

DataOps SQL ML ML 52

Pickl AI

MAY 31, 2023

You should be skilled in using a variety of tools including SQL and Python libraries like Pandas. Tools such as Matplotlib, Seaborn, and Tableau may help you in creating useful visualisations that make challenging data more readily available and understandable to others.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

APRIL 2, 2024

SQL (Structured Query Language): Language for managing and querying relational databases. Tableau/Power BI: Visualization tools for creating interactive and informative data visualizations. Hadoop/Spark: Frameworks for distributed storage and processing of big data.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52