What are the current technologies used in data analytics?

Question

archi jain · Accepted Answer

Current technologies in data analytics include programming languages like Python, R, and SQL, which are used for data manipulation and analysis. Machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn enable predictive modeling and deep learning. Big data tools like Hadoop, Apache Spark, and Kafka help process and analyze large datasets. Data visualization platforms like Tableau, Power BI, and D3.js are used to create interactive dashboards and visual reports. Cloud technologies, such as AWS, Google Cloud, and Azure, provide scalable storage and computing resources. Additionally, business intelligence (BI) tools and data warehousing solutions like Snowflake and Redshift play key roles.

shivanshi singh · Answer

Current Technologies in Data Analytics Big Data Technologies: Tools like Hadoop and Apache Spark for processing large datasets. Data Visualization: Software such as Tableau and Power BI for creating visual insights. Machine Learning: Frameworks like TensorFlow and Scikit-learn for predictive modeling. Cloud Analytics: Platforms like AWS and Google Cloud for scalable data solutions. Database Management: SQL (e.g., MySQL) and NoSQL (e.g., MongoDB) systems for data storage. Data Integration: Tools like Apache NiFi for ETL processes. Business Intelligence: Tools like Qlik and Domo for data analysis and visualization. Artificial Intelligence: Enhances analytics with automation and deeper insights. For more insights into these technologies, visit here: https://uncodemy.com/course/data...

Joshua Daniel Scott · Answer

Definitely using a mix of tools! Hadoop and Spark are my go-tos for big data processing. Can't live without Tableau for those slick visualizations. Recently been playing with TensorFlow for some ML models. And of course, everything's running in the cloud on AWS for that scale. MongoDB has been clutch for the unstructured stuff. Eyeing some AI platforms to level up the automation and insights. Always exploring what's new out there to stay ahead of the data game!

Answer

Data analytics is super dependent on cloud tools these days. AWS, GCP, Azure - pick your poison but you gotta be on the cloud to crunch big data. And then of course ya need solid ML frameworks like TensorFlow or PyTorch to build those predictive models. Tableau still rules for data viz. SQL databases aren't going anywhere but more NoSQL options popping up all the time. It's a complex landscape but those are some of the key tech and tools powering modern analytics from what I can tell! Keen to hear other thoughts.

What are the current technologies used in data analytics?

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