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.

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Pickl AI

JANUARY 13, 2025

Introduction The field of Artificial Intelligence (AI) is rapidly evolving, and with it, the job market in India is witnessing a seismic shift. Top 10 AI Jobs in India The field of Artificial Intelligence (AI) continues to expand, creating a variety of job opportunities. Familiarity with SQL for database management.

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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. Big Data Technologies: Hadoop, Spark, etc. ETL Tools: Apache NiFi, Talend, etc.

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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.

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IBM Journey to AI blog

SEPTEMBER 25, 2023

This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. This allowed them to focus on SQL-based query optimization to the nth degree. What is Presto? It also provides features like indexing and caching.”

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Pickl AI

OCTOBER 22, 2024

With SQL support and various applications across industries, relational databases are essential tools for businesses seeking to leverage accurate information for informed decision-making and operational efficiency. SQL enables powerful querying capabilities for data manipulation.

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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.

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IBM Journey to AI blog

JULY 5, 2023

In the case of Hadoop, one of the more popular data lakes, the promise of implementing such a repository using open-source software and having it all run on commodity hardware meant you could store a lot of data on these systems at a very low cost. It gained rapid popularity given its support for data transformations, streaming and SQL.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

Cost-Efficiency By leveraging cost-effective storage solutions like the Hadoop Distributed File System (HDFS) or cloud-based storage, data lakes can handle large-scale data without incurring prohibitive costs. Processing: Relational databases are optimized for transactional processing and structured queries using SQL.

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IBM Journey to AI blog

JULY 6, 2023

Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. It’s unnecessary to know SQL, as programs are written in R, Java, SAS and other programming languages. What is machine learning? Machine learning and deep learning are both subsets of AI.

Machine Learning 70

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Pickl AI

DECEMBER 4, 2024

The rise of advanced technologies such as Artificial Intelligence (AI), Machine Learning (ML) , and Big Data analytics is reshaping industries and creating new opportunities for Data Scientists. Focus on Python and R for Data Analysis, along with SQL for database management. Here are five key trends to watch.

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Pickl AI

NOVEMBER 5, 2024

Tableau supports many data sources, including cloud databases, SQL databases, and Big Data platforms. Tableau’s data connectors include Salesforce, Google Analytics, Hadoop, Amazon Redshift, and others catering to enterprise-level data needs. This makes it an excellent choice for businesses with a diverse tech stack.

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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. Like their counterparts in the machine learning world, engineers need to know a variety of scripted languages such as SQL for database management, Scala, Java, and of course Python.

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IBM Journey to AI blog

JANUARY 18, 2023

Furthermore, data warehouse storage cannot support workloads like Artificial Intelligence (AI) or Machine Learning (ML), which require huge amounts of data for model training. By the time the data is ready for analysis, the insights it can yield will be stale relative to the current state of transactional systems.

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ODSC - Open Data Science

JANUARY 7, 2025

While knowing Python, R, and SQL is expected, youll need to go beyond that. Similar to previous years, SQL is still the second most popular skill, as its used for many backend processes and core skills in computer science and programming. Employers arent just looking for people who can program.

Data Scientist 40

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Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. You should be skilled in using a variety of tools including SQL and Python libraries like Pandas. It is critical for knowing how to work with huge data sets efficiently.

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ODSC - Open Data Science

MARCH 5, 2025

Once defined by statistical models and SQL queries, todays data practitioners must navigate a dynamic ecosystem that includes cloud computing, software engineering best practices, and the rise of generative AI. In the ever-expanding world of data science, the landscape has changed dramatically over the past two decades.

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