Smart Data Collective

NOVEMBER 8, 2020

Unlike the old days where data was readily stored and available from a single database and data scientists only needed to learn a few programming languages, data has grown with technology. Understand the Databases. As a data engineer, you will be primarily working on databases. Forging a Career Path in the Field of Data Science.

Data Engineering 104

Data Engineering Data Engineering Data Engineering Data Engineer 104

phData

MARCH 7, 2023

The task of keeping multiple databases in sync so that data is accurate, up-to-date, and highly available is every data consumer’s biggest challenge. Oracle is one of the largest IT companies whose flagship product, Oracle Database, is a relational database management system. What is Oracle? What is Oracle GoldenGate?

Hadoop 59

Hadoop Database Data Warehouse AWS 59

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Precisely

MARCH 9, 2023

Hadoop, Snowflake, Databricks and other products have rapidly gained adoption. We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Big Data 59

ODSC - Open Data Science

MAY 31, 2023

Commonly used technologies for data storage are the Hadoop Distributed File System (HDFS), Amazon S3, Google Cloud Storage (GCS), or Azure Blob Storage, as well as tools like Apache Hive, Apache Spark, and TensorFlow for data processing and analytics.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

Pickl AI

NOVEMBER 4, 2024

They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes. Data Modelling Data modelling is creating a visual representation of a system or database. Physical Models: These models specify how data will be physically stored in databases.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

DagsHub

DECEMBER 11, 2023

DVC lacks crucial relational database features, making it an unsuitable choice for those familiar with relational databases. Dolt Created in 2019, Dolt is an open-source tool for managing SQL databases that uses version control similar to Git. It versions tables instead of files and has a SQL query interface for those tables.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

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 Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. This includes structured data (like databases), semi-structured data (like XML files), and unstructured data (like text documents and videos). Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. This includes structured data (like databases), semi-structured data (like XML files), and unstructured data (like text documents and videos). Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

JUNE 7, 2024

It involves retrieving data from various sources, such as databases, spreadsheets, or even cloud storage. The ETL tool must work with your current systems, support your existing databases and applications, and be able to connect to various data sources. It supports a wide range of databases and provides robust ETL capabilities.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Pickl AI

JANUARY 13, 2025

Key Skills Experience with cloud platforms (AWS, Azure). Familiarity with SQL for database management. Strong understanding of database management systems (e.g., Hadoop , Apache Spark ) is beneficial for handling large datasets effectively. They ensure that AI systems are scalable and efficient.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 5, 2024

Its popularity stems from its user-friendly interface and seamless integration with widely used Microsoft applications like Excel and Azure, making it highly accessible for organisations already using Microsoft products. Tableau supports many data sources, including cloud databases, SQL databases, and Big Data platforms.

Power BI 52

Power BI Tableau Business Intelligence Business Intelligence 52

Mlearning.ai

MARCH 15, 2023

Familiarity with Databases; SQL for structured data, and NOSQL for unstructured data. Experience with cloud platforms like; AWS, AZURE, etc. Knowledge of big data platforms like; Hadoop and Apache Spark. Knowledge of big data platforms like; Hadoop and Apache Spark. Basic programming knowledge in R or Python.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

IBM Journey to AI blog

JANUARY 18, 2023

This is an architecture that’s well suited for the cloud since AWS S3 or Azure DLS2 can provide the requisite storage. data platforms and databases), all interacting with one another to provide greater value. A data fabric can consist of multiple data warehouses, data lakes, IoT/Edge devices and transactional databases.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

DagsHub

OCTOBER 23, 2024

Data can come from different sources, such as databases or directly from users, with additional sources, including platforms like GitHub, Notion, or S3 buckets. Vector Databases Vector databases help store unstructured data by storing the actual data and its vector representation. mp4,webm, etc.), and audio files (.wav,mp3,acc,

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

The MLOps Blog

JANUARY 23, 2023

But, it is not rare that data engineers and database administrators process, control, and store terabytes of data in projects that are not related to machine learning. Data from different formats, databases, and sources are combined together for modeling. It supports most major cloud providers, such as AWS, GCP, and Azure.

ML 52

ML ML Data Lakes Machine Learning 52

DagsHub

NOVEMBER 11, 2024

Unlike structured data, unstructured data doesn’t fit neatly into predefined models or databases, making it harder to analyse using traditional methods. While sensor data is typically numerical and has a well-defined format, such as timestamps and data points, it only fits the standard tabular structure of databases.

AI 52

AI AI Data Lakes Database 52

Pickl AI

NOVEMBER 28, 2024

databases, CSV files). Cloud platforms like AWS , Google Cloud Platform (GCP), and Microsoft Azure provide managed services for Machine Learning, offering tools for model training, storage, and inference at scale. Structured data refers to data organised in tables or spreadsheets (e.g.,

Machine Learning 52

Machine Learning Machine Learning ML ML 52

The MLOps Blog

MAY 31, 2023

So, a better database architecture would be to maintain multiple tables where one of the tables maintains the past 3 months history with session-level details, whereas other tables may contain weekly aggregated click, ATC, and order data. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data.

ML 59

ML ML Algorithm Machine Learning 59

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.

Deep Learning 195

Deep Learning Deep Learning Machine Learning Machine Learning 195

Pickl AI

DECEMBER 4, 2024

Focus on Python and R for Data Analysis, along with SQL for database management. Gain Experience with Big Data Technologies With the rise of Big Data, familiarity with technologies like Hadoop and Spark is essential. AWS or Azure) will be increasingly important as more organisations migrate their operations online.

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. SQL (Structured Query Language): Language for managing and querying relational databases. Hadoop/Spark: Frameworks for distributed storage and processing of big data.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

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. Key Features : Scalability : Hadoop can handle petabytes of data by adding more nodes to the cluster. Use Cases : Yahoo!

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

Pickl AI

MARCH 19, 2025

A data engineer creates and manages the pipelines that transfer data from different sources to databases or cloud storage. Data Storage : Keeping data safe in databases or cloud platforms. It allows them to retrieve, manipulate, and manage structured data in relational databases. What Does a Data Engineer Do?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52