Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

Big Data 52

Big Data Big Data Big Data Analytics Big Data 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.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Data Science Blog

NOVEMBER 15, 2023

The trend towards powerful in-house cloud platforms for data and analysis ensures that large volumes of data can increasingly be stored and used flexibly. This aspect can be applied well to Process Mining, hand in hand with BI and AI. It is based on a German SAP ERP configuration with customized processes.

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245

Pickl AI

DECEMBER 25, 2024

Key Tools and Techniques Business Analytics employs various tools and techniques to process and interpret data effectively. Dashboards, such as those built using Tableau or Power BI , provide real-time visualizations that help track key performance indicators (KPIs). Data Scientists require a robust technical foundation.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

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. That’s where SQL comes in, enabling data analysts to extract, manipulate and analyse data from multiple sources.

Data Analyst 52

Data Analyst SQL Data Analysis Data Analysis 52

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. Skills in manipulating and managing data are also necessary to prepare the data for analysis.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Analytics Vidhya

MAY 21, 2023

Introduction Not a single day passes without us getting to hear the word “data.” This is precisely what happens in data analytics. People equipped with the […] The post 10 Best Data Analytics Projects appeared first on Analytics Vidhya. It is almost as if our lives revolve around it. Don’t they?

Analytics 357

Analytics Analytics Power BI Hadoop 357

Data Science Dojo

JULY 3, 2024

Data Visualization : Techniques and tools to create visual representations of data to communicate insights effectively. Tools like Tableau, Power BI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Tools and frameworks like Scikit-Learn, TensorFlow, and Keras are often covered.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Smart Data Collective

JULY 22, 2019

Automating your data processing routine can offer your business a lot of benefits. BI tools use the Big Data approach and apply it to your company data. Microsoft Power BI. Microsoft Power BI is a free and powerful business intelligence tool from a world-leading software giant Microsoft.

Business Intelligence 103

Business Intelligence Business Intelligence Power BI Tableau 103

Smart Data Collective

MAY 20, 2019

We’re well past the point of realization that big data and advanced analytics solutions are valuable — just about everyone knows this by now. Big data alone has become a modern staple of nearly every industry from retail to manufacturing, and for good reason. But it’s not the only skill necessary to thrive.

Analytics 111

Analytics Analytics Data Analyst Machine Learning 111

ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential. Cloud Services: Google Cloud Platform, AWS, Azure.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Mlearning.ai

MARCH 15, 2023

Data professionals are in high demand all over the globe due to the rise in big data. The roles of data scientists and data analysts cannot be over-emphasized as they are needed to support decision-making. This article will serve as an ultimate guide to choosing between Data Science and Data Analytics.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Data scientists will typically perform data analytics when collecting, cleaning and evaluating data.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. 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 Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

APRIL 29, 2024

You can also read about Top 10 Data Science Interview Questions and Answers 2024’s Top Power BI Interview Questions Top DBMS Interview Questions: Basic Level These DBMS interview questions for freshers establish your foundational understanding of DBMS concepts: 1. What are the different types of joins in SQL?

Database 52

Database SQL Power BI Big Data 52

Pickl AI

FEBRUARY 27, 2024

It delves into data analysis techniques to interpret financial trends effectively, including statistical analysis and data visualization. Participants learn to leverage tools like Excel, Python, and SQL for data manipulation and analysis, enabling better financial modeling and forecasting decision-making.

Data Visualization 52

Data Visualization Data Analyst SQL Data Analysis 52

Pickl AI

DECEMBER 4, 2024

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally. The field has evolved significantly from traditional statistical analysis to include sophisticated Machine Learning algorithms and Big Data technologies.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 5, 2024

These courses introduce you to Python, Statistics, and Machine Learning , all essential to Data Science. Starting with these basics enables a smoother transition to more specialised topics, such as Data Visualisation, Big Data Analysis , and Artificial Intelligence. Data Science Course by Pickl.AI

Data Science 52

Data Science Machine Learning Machine Learning Python 52

Pickl AI

JUNE 12, 2023

A Data Scientist requires to be able to visualize quickly the data before creating the model and Tableau is helpful for that. Tableau is useful for summarising the metrics of success. Disadvantages of Tableau for Data Science However, apart from the advantages, Tableau for Data Science also has its own disadvantages.

Tableau 52

Tableau Data Science Data Scientist Data Analysis 52

Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

SEPTEMBER 5, 2024

Unified Data Services: Azure Synapse Analytics combines big data and data warehousing, offering a unified analytics experience. Azure’s global network of data centres ensures high availability and performance, making it a powerful platform for Data Scientists to leverage for diverse data-driven projects.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Pickl AI

FEBRUARY 19, 2025

Big Data: Refers to vast sets of data that traditional tools cannot process; commonly used in industries like social media, e-commerce, and healthcare. Data Visualisation: Presents data in visual formats, such as graphs and charts; helps identify patterns and trends for better decision-making.

Data Science 52

Data Science Analytics Analytics Machine Learning 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

Alation

JANUARY 17, 2023

Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? Reverse ETL tools.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Pickl AI

APRIL 2, 2024

Understanding Data Structured Data: Organized data with a clear format, often found in databases or spreadsheets. Unstructured Data: Data without a predefined structure, like text documents, social media posts, or images. Data Cleaning: Process of identifying and correcting errors or inconsistencies in datasets.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Pickl AI

JANUARY 28, 2025

They store structured data in a format that facilitates easy access and analysis. Data Lakes: These store raw, unprocessed data in its original format. They are useful for big data analytics where flexibility is needed. These tools work together to facilitate efficient data management and analysis processes.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

ODSC - Open Data Science

JANUARY 7, 2025

Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well. While knowing Python, R, and SQL is expected, youll need to go beyond that. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

JULY 18, 2024

Relational databases use SQL for querying, which can be complex and rigid. In contrast, MongoDB uses a more straightforward query language that works well with JSON data structures. It also supports horizontal scaling through sharding, making it suitable for handling large volumes of data. What Is a Collection in MongoDB?

Database 52

Database SQL Data Analyst Database Administration 52