Ascend.io

OCTOBER 28, 2024

What is Data Transformation? Data transformation is the process of converting raw data into a usable format to generate insights. It involves cleaning, normalizing, validating, and enriching data, ensuring that it is consistent and ready for analysis.

Raw Data 52

Raw Data Aggregated Data Data Pipeline Data Validation 52

ProjectPro

JUNE 6, 2025

No, that is not the only job in the data world. Data professionals who work with raw data, like data engineers, data analysts, machine learning scientists , and machine learning engineers , also play a crucial role in any data science project. End-to-end analytics pipeline design.

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

ThoughtSpot

APRIL 22, 2025

Level 2: Understanding your dataset To find connected insights in your business data, you need to first understand what data is contained in the dataset. This is often a challenge for business users who arent familiar with the source data. In this example, were asking, What is our customer lifetime value by state?

BI 59

BI Business Intelligence Datasets Raw Data 59

ProjectPro

JUNE 6, 2025

Today, data engineers are constantly dealing with a flood of information and the challenge of turning it into something useful. The journey from raw data to meaningful insights is no walk in the park. It requires a skillful blend of data engineering expertise and the strategic use of tools designed to streamline this process.

Data Pipeline 49

Data Pipeline Google Cloud Kafka AWS 49

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. To try and predict this, an extensive dataset including anonymised details on the individual loanee and their historical credit history are included. Get the Dataset. Introduction.

Machine Learning 137

Machine Learning Data Science Datasets Data Lake 137

ProjectPro

JUNE 6, 2025

Building data pipelines is a core skill for data engineers and data scientists as it helps them transform raw data into actionable insights. You’ll walk through each stage of the data processing workflow, similar to what’s used in production-grade systems.

Python 40

Python Building PostgreSQL Raw Data 40

Teradata

MAY 30, 2025

The scripts demonstrate how to easily extract data from a source into Vantage with Airbyte, perform necessary transformations using dbt, and seamlessly orchestrate the entire pipeline with Dagster. Setting up the dbt project dbt (data build tool) allows you to transform your data by writing, documenting, and executing SQL workflows.

Data Integration 52

Data Integration Raw Data Metadata Data Pipeline 52

ProjectPro

JUNE 6, 2025

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 66

AWS Scala Data Lake Metadata 66

ProjectPro

JUNE 6, 2025

However, building and maintaining a scalable data science pipeline comes with challenges like data quality , integration complexity, scalability, and compliance with regulations like GDPR. The journey begins with collecting data from various sources, including internal databases, external repositories, and third-party providers.

Data Science 40

Data Science Building Data Lake AWS 40

Edureka

MAY 27, 2025

Transform Your Data Analytics with Microsoft Fabric! Microsoft Fabric removes silos and offers a uniform experience for data engineers, scientists, analysts, and business users by integrating these elements. From raw data to insights for decision-making, it’s all on one platform.

Architecture 52

Architecture BI Data Lake Government 52

ProjectPro

JUNE 6, 2025

These platforms facilitate effective data management and other crucial Data Engineering activities. This blog will give you an overview of the GCP data engineering tools thriving in the big data industry and how these GCP tools are transforming the lives of data engineers.

Data Engineering 40

Data Engineering Data Engineer Engineering Google Cloud 40

ProjectPro

JUNE 6, 2025

With the data integration market expected to reach $19.6 billion by 2026 and 94% of organizations reporting improved performance from data insights, mastering DBT is critical for aspiring data professionals. This is helpful for keeping track of external dependencies and applying testing or documentation to raw data inputs.

Raw Data 40

Raw Data SQL Datasets Data Pipeline 40

ProjectPro

JUNE 6, 2025

While data science is the most hyped-up career path in the data industry, it certainly isn't the only one. You can consider many other high-paying career options as a data enthusiast. This blog will take you through a relatively new career title in the data industry — AI Engineer.

Engineering 75

Engineering Software Engineer Software Engineering Deep Learning 75

ProjectPro

JUNE 6, 2025

Want to step up your big data analytics game like a pro? Read this dbt (data build tool) Snowflake tutorial blog to leverage the combined potential of dbt, the ultimate data transformation tool, and Snowflake, the scalable cloud data warehouse, to create efficient data pipelines.

Pipeline-centric 40

Pipeline-centric Database-centric Raw Data Data Warehouse 40

Preset

NOVEMBER 19, 2023

Customers Contact Sales Log In Try for Free DEEP DIVE Comparing Apache Superset and Mode Analytics Satoko Nakayama November 20, 2023 Subscribe In this blog, we will compare the functionalities of two modern business intelligence platforms: Mode Analytics and open-source Apache Superset (or its cloud-hosted version, Preset Cloud , where applicable).

BI 52

BI Business Intelligence SQL Python 52

Maxime Beauchemin

AUGUST 28, 2017

Traditionalists would suggest starting a data stewardship and ownership program, but at a certain scale and pace, these efforts are a weak force that are no match for the expansion taking place. This yet-to-be-built framework would have a set of hard constraints, but in return will provide strong guarantees while enforcing best practices.

Data Engineering 174

Data Engineering Data Engineer Engineering Software Engineer 174

Edureka

JANUARY 2, 2025

Power BI’s extensive modeling, real-time high-level analytics, and custom development simplify working with data. You will often need to work around several features to get the most out of business data with Microsoft Power BI. Additionally, it manages sizable datasets without causing Power BI to crash or perform less quickly.

BI 52

BI Datasets Business Intelligence Data Analysis 52

ProjectPro

JUNE 6, 2025

Data Analytics Data Science , Data Engineering, and Data Analytics are interconnected but distinct domains within data management and analysis. Data Science involves extracting meaningful insights from large and complex datasets using statistical, mathematical, and programming techniques.

Data Science 52

Data Science Portfolio Programming Language Data 52

ProjectPro

JUNE 6, 2025

FAQs ETL vs ELT for Data Engineers ETL (Extract, Transform, and Load) and ELT (Extract, Load, and Load) are two widespread data integration and transformation approaches that help in building data pipelines. Organizations often use ETL, ELT, or a combination of the two data transformation approaches. What is ETL?

Data Engineering 40

Data Engineering Data Engineer Engineering Data Lake 40

Preset

AUGUST 8, 2023

In this blog post, we will compare the functionalities of ThoughtSpot and Superset to help you identify the right BI solution for your organization. Additionally, its in-memory calculation engine allows users to perform computations on large datasets. Technical users (data professionals) and non-technical users (business users).

Database-centric 52

Database-centric BI Business Intelligence SQL 52

ProjectPro

JUNE 6, 2025

Struggling to handle messy data silos? Fear not, data engineers! This blog is your roadmap to building a data integration bridge out of chaos, leading to a world of streamlined insights. Think of the data integration process as building a giant library where all your data's scattered notebooks are organized into chapters.

Data Integration 40

Data Integration Project Data Lake Hospitality 40

ProjectPro

JUNE 6, 2025

Ready to ride the data wave from “ big data ” to “big data developer”? This blog is your ultimate gateway to transforming yourself into a skilled and successful Big Data Developer, where your analytical skills will refine raw data into strategic gems.

Big Data 40

Big Data Hadoop Scala NoSQL 40

ProjectPro

JUNE 6, 2025

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. A pipeline may include filtering, normalizing, and data consolidation to provide desired data.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. They have a well-researched collection of data such as ratings, reviews, timestamps, price, category information, customer likes, and dislikes.

Machine Learning 69

Machine Learning Project Datasets Algorithm 69

Rockset

MARCH 27, 2019

The application you're implementing needs to analyze this data, combining it with other datasets, to return live metrics and recommended actions. But how can you interrogate the data and frame your questions correctly if you don't understand the shape of your data? Where do you begin?

Raw Data 40

Raw Data SQL NoSQL Datasets 40

ProjectPro

JUNE 6, 2025

A data engineer can fulfill the above-mentioned responsibilities only if they possess a suitable skill set. And if you are now searching for a list of that highlights those skills, head over to the next section of this blog. In such instances, raw data is available in the form of JSON documents, key-value pairs, etc.,

Data Engineering 49

Data Engineering Data Engineer Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

Data science is a vast field with several job roles emerging within it. This blog post will explore the top 15 data science roles worth pursuing. According to LinkedIn's Emerging Jobs Report, data science is the fastest-growing industry in the world. The market size is expected to reach $230.80 billion by 2026 from $37.9

Data Science 56

Data Science Data Mining Data Architect BI 56

ProjectPro

JUNE 6, 2025

This blog presents the topmost useful machine learning applications in finance to help you understand how financial markets thrive by adopting AI and ML solutions. Use the Pandas data frame to read and store your data. Also, remove all missing and NaN values from the dataset, as incomplete data is unnecessary.

Finance 75

Finance Machine Learning Project Banking 75

ProjectPro

JUNE 6, 2025

And, if you are one of those who are clueless about where to start learning about AI, then Data Analysis is the topic you should explore. Read this blog to understand how to learn Data Analysis in the shortest possible time. And this is where data analysis comes into play. which makes analyzing large datasets trivial.

Data Analysis 40

Data Analysis IT Programming Language Algorithm 40

ProjectPro

JUNE 6, 2025

The decrease in the accuracy of a deep learning model after a few epochs implies that the model is learning from the characteristics of the dataset and not considering the features. Epoch refers to the iteration where the complete dataset is passed forward and backward through the neural network only once.

Deep Learning 65

Deep Learning Datasets Machine Learning Algorithm 65

ProjectPro

JUNE 6, 2025

If you’re curious to learn more about how data analysis is done at Uber to ensure positive experiences for riders while making the ride profitable for the company - Get your hands dirty working with the Uber dataset to gain in-depth insights. The Uber Datasets We will perform data analysis on two types of rider data from Uber.

Machine Learning 45

Machine Learning Data Analysis Project Datasets 45

ProjectPro

JUNE 6, 2025

This blog post provides an overview of the top 10 data engineering tools for building a robust data architecture to support smooth business operations. Table of Contents What are Data Engineering Tools? This speeds up data processing by reducing disc read and write times.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

ProjectPro

JUNE 6, 2025

Picture this: a world where you decipher complex datasets, predict future trends, and easily build data-driven solutions- all thanks to the power of Azure cloud services. Want to enhance your knowledge of Azure services that will lead to an exciting career as an Azure Data Scientist?

Machine Learning 40

Machine Learning Data Science Certification Raw Data 40

ProjectPro

JUNE 6, 2025

Using Artificial Intelligence (AI) in the Data Analytics process is the first step for businesses to understand AI's potential. This blog revolves around helping individuals realize this potential through its applications, advantages, and project examples. from 2022 to 2030.

Data Analytics 40

Data Analytics Healthcare Machine Learning Datasets 40

Edureka

MARCH 15, 2025

By learning the details of smaller datasets, they better balance task-specific performance and resource efficiency. It is seamlessly integrated across Meta’s platforms, increasing user access to AI insights, and leverages a larger dataset to enhance its capacity to handle complex tasks. What are Small language models?

Entertainment 74

Entertainment Education Retail Healthcare 74

ProjectPro

JUNE 6, 2025

Managing an end-to-end ML project isn't just about building models; it involves navigating through multiple stages, such as identifying the right problem, sourcing and cleaning data, developing a reliable model, and deploying it effectively. Data collection is about gathering the raw data needed to train and evaluate the model.

Machine Learning 40

Machine Learning Project Building Raw Data 40

ProjectPro

JUNE 6, 2025

In an era where data is abundant, and algorithms are aplenty, the MLops pipeline emerges as the unsung hero, transforming raw data into actionable insights and deploying models with precision. This blog is your key to mastering the vital skill of deploying MLOps pipelines in data science.

Building 40

Building Machine Learning Raw Data Data Collection 40