Women in Big Data

OCTOBER 9, 2024

Batch Processing: For large datasets, frameworks like Apache Hadoop MapReduce or Apache Spark are used. Visualization and Reporting (Presentation): Data visualization tools like Tableau or custom dashboards enable easy interpretation of data. This phase ensures quality and consistency using frameworks like Apache Spark or AWS Glue.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

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

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Data Visualization: Matplotlib, Seaborn, Tableau, etc. Big Data Technologies: Hadoop, Spark, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Mlearning.ai

FEBRUARY 22, 2023

This could involve using a distributed file system, such as Hadoop, or a cloud-based storage service, such as Amazon S3. This could involve using tools like Tableau or Power BI to create visualizations and dashboards. This could involve batch processing or real-time streaming, depending on your needs.

Big Data 52

Big Data Big Data Power BI Hadoop 52

Mlearning.ai

MARCH 15, 2023

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. Experience with cloud platforms like; AWS, AZURE, etc. Basic programming knowledge in R or Python.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

DataSeries

AUGUST 15, 2024

Hadoop, Spark). 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

Dataconomy

JULY 24, 2023

Tools like Tableau, Matplotlib, Seaborn, or Power BI can be incredibly helpful. Learn relevant tools Familiarize yourself with data science tools and platforms, such as Tableau for data visualization, or Hadoop for big data processing. This is where data visualization comes in.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Data Science Dojo

JULY 3, 2024

Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. R : Often used for statistical analysis and data visualization.

Data Science 195

Data Science Machine Learning Machine Learning Data Visualization 195

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. js and Tableau Data science, data analytics and IBM Practicing data science isn’t without its challenges. Your skill set should include the ability to write in the programming languages Python, SAS, R and Scala.

Data Science 98

Data Science Analytics Analytics Data Scientist 98

Alation

FEBRUARY 12, 2020

More than 300 data analysts and 5,000 business users were accessing eBay’s analytics platform directly and through more than 10,000 reports in Tableau and 5,000 in MicroStrategy.

Machine Learning 52

Machine Learning Machine Learning Hadoop Analytics 52

Pickl AI

MAY 29, 2024

Proficiency with tools like Tableau , Matplotlib , and ggplot2 helps create charts, graphs, and dashboards that effectively communicate insights to stakeholders. Big Data Technologies (Hadoop, Spark) Hadoop and Spark are super helpful for managing big data. Data Visualisation Visualisation of data is a critical skill.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 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 Data Pipeline Analytics 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

FEBRUARY 28, 2023

At length, use Hadoop, Spark, and tools like Pig and Hive to develop big data infrastructures. Data Analyst vs Data Scientist: Required Skills Some common skills necessary for Data Analysts and Data Scientists include Data Mining , Data Warehousing , Math, Statistics, Computer Science, Tableau and Data Visualisation.

Data Analyst 52

Data Analyst Data Scientist Data Science Computer Science 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

Alation

FEBRUARY 13, 2020

This meant a large Hadoop deployment, self-service analytics tools available to every employee with Tableau, and a data catalog from Alation. A team of data stewards certify reports and dashboards for accuracy and publish Unified Data Sets to all employees for use in tools like Tableau.

Decision Science 59

Decision Science Analytics Analytics Data Science 59

Pickl AI

MARCH 10, 2023

Some of the tools used by Data Science in 2023 include statistical analysis system (SAS), Apache, Hadoop, and Tableau. It contains data clustering, classification, anomaly detection and time-series forecasting. Others have Knime, RapidMiner, PowerBI, Python, Jupyter, Microsoft HDInsight, etc.

Data Scientist 52

Data Scientist Data Science Apache Hadoop Machine Learning 52

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

Pickl AI

APRIL 18, 2023

Here is what you need to add to your resume Analysed Built Conducted Created Collaborated Developed Integrated Led Managed Partnered Support Designed Showcase Your Technical Skills In addition to using the right words and phrases in your resume, you should also highlight the key skills.

Data Science 52

Data Science Machine Learning Machine Learning Data Scientist 52

Pickl AI

JULY 10, 2023

Packages like dplyr, data.table, and sparklyr enable efficient data processing on big data platforms such as Apache Hadoop and Apache Spark. Esquisse: One of the most essential tableau features that has been introduced within the R libraries is Esquisse. You can simply drag and drop to complete your visualisation in minutes.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

phData

FEBRUARY 5, 2024

Matillion Matillion is a complete ETL tool that integrates with an extensive list of pre-built data source connectors, loads data into cloud data environments such as Snowflake, and then performs transformations to make data consumable by analytics tools such as Tableau and PowerBI. Get to know all the ins and outs of your upcoming migration.

SQL 52

SQL Database Data Quality Data Warehouse 52

Pickl AI

MAY 31, 2023

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 Visualisation: The ability to present insights effectively through visualisation of data is an appreciated skill.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Alation

JANUARY 25, 2022

Alation partners such as Dataiku, Trifacta, and Tableau are perfect examples. These approaches extend the continuum of enterprise data warehouses, federated data marts, big data (Hadoop), and virtualization on top of distributed cloud file storage. How can data users navigate and understand such a complex landscape predictably?

DataOps 52

DataOps SQL ML ML 52

Mlearning.ai

AUGUST 18, 2023

Get in touch with us to discuss your needs and wants and bring your ideas to life.

Data Science 52

Data Science Data Scientist Internet of Things Apache Hadoop 52

Data Science Dojo

MAY 24, 2024

Java is also widely used in big data technologies, supported by powerful Java-based tools like Apache Hadoop and Spark, which are essential for data processing in AI. Big Data Technologies With the growth of data-driven technologies, AI engineers must be proficient in big data platforms like Hadoop, Spark, and NoSQL databases.

AI 195

AI AI Deep Learning Deep Learning 195

Alation

FEBRUARY 20, 2020

A “catalog-first” approach to business intelligence enables both empowerment and accuracy; and Alation has long enabled this combination over Tableau. Alation’s deep integration with tools like MicroStrategy and Tableau provides visibility into the complete data pipeline: from storage through visualization.

Data Governance 52

Data Governance Tableau Hadoop Data Pipeline 52

Pickl AI

APRIL 2, 2024

Tableau/Power BI: Visualization tools for creating interactive and informative data visualizations. Hadoop/Spark: Frameworks for distributed storage and processing of big data. Tools and Technologies Python/R: Popular programming languages for data analysis and machine learning.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Alation

FEBRUARY 20, 2020

Today, you have Tableau, empowering any analyst to create a report. Whether using Tableau, Informatica, Excel, MicroStrategy, Hadoop or Teradata to store or prepare data, data is all over the place. Now you have iPhones and YouTube. Again, you lose the filter that comes with central casting. The experience is seamless.

ETL 52

ETL Hadoop Tableau Data Scientist 52