Smart Data Collective

AUGUST 9, 2023

Organizations that use data analysis to improve their profitability can use the following techniques to streamline their operations and reorient their business workflows. Companies that have revenue information stored in a conventional flat spreadsheet might do well to opt for a relational database like MySQL or Postgres.

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Dataconomy

FEBRUARY 25, 2025

This characteristic reflects the growing sources and types of data collected over time. Variety Variety delineates the different data types involved, encompassing structured data like databases, unstructured data such as text and multimedia content, and semi-structured data found in logs and sensor data.

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Big Data Big Data Data Lakes Machine Learning 91

Data Science Dojo

JULY 3, 2024

Here’s a list of key skills that are typically covered in a good data science bootcamp: Programming Languages : Python : Widely used for its simplicity and extensive libraries for data analysis and machine learning. R : Often used for statistical analysis and data visualization.

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Becoming Human

JANUARY 23, 2023

- a beginner question Let’s start with the basic thing if I talk about the formal definition of Data Science so it’s like “Data science encompasses preparing data for analysis, including cleansing, aggregating, and manipulating the data to perform advanced data analysis” , is the definition enough explanation of data science?

Data Science 105

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Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

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Pickl AI

DECEMBER 9, 2024

First, lets understand the basics of Big Data. Key Takeaways Understand the 5Vs of Big Data: Volume, Velocity, Variety, Veracity, Value. Familiarise yourself with essential tools like Hadoop and Spark. Practice coding skills in languages relevant to Big Data roles. Veracity Data reliability and quality vary significantly.

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Women in Big Data

OCTOBER 9, 2024

They can process data in real-time, in batches, or through hybrid methods, allowing organizations to scale operations and complete tasks in a fraction of the time traditional pipelines require. Components of a Big Data Pipeline Data Sources (Collection): Data originates from various sources, such as databases, APIs, and log files.

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Pickl AI

AUGUST 1, 2023

The primary goal of Data Engineering is to transform raw data into a structured and usable format that can be easily accessed, analyzed, and interpreted by Data Scientists, analysts, and other stakeholders. Future of Data Engineering The Data Engineering market will expand from $18.2

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Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineering 52

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Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. Variety Variety indicates the different types of data being generated.

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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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Pickl AI

NOVEMBER 25, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. Variety Variety indicates the different types of data being generated.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JANUARY 13, 2025

Familiarity with SQL for database management. Proficiency in Data Analysis tools for market research. Experience with big data technologies (e.g., Strong understanding of database management systems (e.g., Data Management and Processing Develop skills in data cleaning, organisation, and preparation.

AI 52

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Pickl AI

NOVEMBER 15, 2023

What Is Data Lake? A Data Lake is a centralized repository that allows businesses to store vast volumes of structured and unstructured data at any scale. Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible.

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Dataconomy

JULY 25, 2023

Here is why: Skill and knowledge requirements: Data science is a multidisciplinary field that demands proficiency in statistics, programming languages (such as Python or R), machine learning algorithms, data visualization, and domain expertise. Conclusion: Is data science a good career?

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Pickl AI

FEBRUARY 28, 2023

Significantly, Data Science experts have a strong foundation in mathematics, statistics, and computer science. Furthermore, they must be highly efficient in programming languages like Python or R and have data visualization tools and database expertise. Who is a Data Analyst?

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Pickl AI

JULY 18, 2023

SQL: Mastering Data Manipulation Structured Query Language (SQL) is a language designed specifically for managing and manipulating databases. While it may not be a traditional programming language, SQL plays a crucial role in Data Science by enabling efficient querying and extraction of data from databases.

Data Science 52

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Pickl AI

MAY 29, 2024

Data Science has also been instrumental in addressing global challenges, such as climate change and disease outbreaks. Data Science has been critical in providing insights and solutions based on Data Analysis. Skills Required for a Data Scientist Data Science has become a cornerstone of decision-making in many industries.

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Pickl AI

AUGUST 21, 2024

Data Collection : The crawler collects information from each page it visits, including the page title, meta tags, headers, and other relevant data. Crawlers then store this information in a database for indexing. Structured data can be easily imported into databases or analytical tools.

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Pickl AI

JANUARY 28, 2025

They encompass all the origins from which data is collected, including: Internal Data Sources: These include databases, enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and flat files within an organization. Data can be structured (e.g., databases), semi-structured (e.g.,

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

DagsHub

OCTOBER 23, 2024

There are 5 stages in unstructured data management: Data collection Data integration Data cleaning Data annotation and labeling Data preprocessing Data Collection The first stage in the unstructured data management workflow is data collection. mp4,webm, etc.), and audio files (.wav,mp3,acc,

Machine Learning 52

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Pickl AI

JUNE 19, 2024

This is because these fields provide a strong foundation in the quantitative and analytical skills crucial for Data Science course eligibility. These skills translate well to the Data Science domain. Look for opportunities in business intelligence, market research, or any role that involves data analysis and interpretation.

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Pickl AI

NOVEMBER 5, 2024

Data Connectivity Tableau and Power BI offer robust data connectivity, but some differences exist. Tableau supports many data sources, including cloud databases, SQL databases, and Big Data platforms. Tableau supports integrations with third-party tools, including Salesforce, Hadoop, and Google Analytics.

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DagsHub

NOVEMBER 11, 2024

Types of Unstructured Data As unstructured data grows exponentially, organisations face the challenge of processing and extracting insights from these data sources. Unlike structured data, unstructured data doesn’t fit neatly into predefined models or databases, making it harder to analyse using traditional methods.

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Pickl AI

MAY 15, 2023

The systems are designed to ensure data integrity, concurrency and quick response times for enabling interactive user transactions. In online analytical processing, operations typically consist of major fractions of large databases. What is the key objective of data analysis?

Machine Learning 52

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Pickl AI

OCTOBER 10, 2024

Talend Talend is a leading data integration platform known for its extensive tools for transforming, cleansing, and integrating data across multiple sources. It integrates well with cloud services, databases, and big data platforms like Hadoop, making it suitable for various data environments.

Data Quality 52

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Pickl AI

OCTOBER 14, 2024

Additionally, a strong foundation in programming languages like Python or R and familiarity with Data Analysis concepts can enhance your application. Core Subjects Master’s programs in Data Science typically include a comprehensive set of core subjects that form the foundation of the field.

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Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

Big Data 91

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Pickl AI

NOVEMBER 28, 2024

Data Collection: Sources and Types of Data Data comes in various forms , broadly categorised as structured and unstructured. Structured data refers to data organised in tables or spreadsheets (e.g., databases, CSV files). Data Cleaning and Preprocessing The first step in data preprocessing is cleaning.

Machine Learning 52

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The MLOps Blog

MAY 31, 2023

The Clickstream Data usually contains <SessionId, User, Query, Item, Click, ATC, Order> Maintaining session-level data for each user over a long history could be overkill, and ML model development might not always require that level of granular data. How to set up a data processing platform?

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Data Science Dojo

MAY 24, 2024

Navigate through 6 Popular Python Libraries for Data Science R R is another important language, particularly valued in statistics and data analysis, making it useful for AI applications that require intensive data processing. Python’s versatility allows AI engineers to develop prototypes quickly and scale them with ease.

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Pickl AI

DECEMBER 4, 2024

Augmented Analytics Augmented analytics is revolutionising the way businesses analyse data by integrating Artificial Intelligence (AI) and Machine Learning (ML) into analytics processes. Understand data structures and explore data warehousing concepts to efficiently manage and retrieve large datasets.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 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. Hadoop/Spark: Frameworks for distributed storage and processing of big data.

Data Science 52

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Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. By harnessing the power of Big Data tools, organisations can transform raw data into actionable insights that foster innovation and competitive advantage.

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Pickl AI

MARCH 19, 2025

Without data engineering , companies would struggle to analyse information and make informed decisions. What Does a Data Engineer Do? A data engineer creates and manages the pipelines that transfer data from different sources to databases or cloud storage. How is Data Engineering Different from Data Science?

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