Edureka

APRIL 22, 2025

Azure, Power BI, and Microsoft 365 are already widely used by ShopSmart, which is in line with Fabric’s integrated ecosystem. The alternative, however, provides more multi-cloud flexibility and strong performance on structured data. Its multi-cluster shared data architecture is one of its primary features.

Pipeline-centric 52

Pipeline-centric BI Data Lake Google Cloud 52

ProjectPro

JUNE 6, 2025

allow data engineers to acquire, analyze, process, and manage huge volumes of data simply and efficiently. Visualization tools like Tableau and Power BI allow data engineers to generate valuable insights and create interactive dashboards. It can also access structured and unstructured data from various sources.

Data Engineering 45

Data Engineering Data Engineer Engineering Kafka 45

Edureka

MAY 27, 2025

OneLake Data Lake OneLake provides a centralized data repository and is the fundamental storage layer of Microsoft Fabric. It preserves security and governance while facilitating smooth data access across all Fabric services. Throughout the Fabric ecosystem, it facilitates smooth orchestration.

Architecture 52

Architecture BI Data Lake Business Intelligence 52

ProjectPro

JUNE 6, 2025

Data Analysis Tools- How does Big Data Analytics Benefit Businesses? Top 15 Data Analysis Tools to Explore in 2025 | Trending Data Analytics Tools 1. Power BI 4. Google Data Studio 10. Identifying patterns is one of the key purposes of statistical data analysis. more accessible. Apache Spark 6.

Data Analysis Tools 45

Data Analysis Tools Data Analysis BI R (Programming) 45

ProjectPro

JUNE 6, 2025

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace. What is Business Intelligence?

Business Intelligence 56

Business Intelligence BI Data Mining Raw Data 56

ProjectPro

JUNE 6, 2025

Traditional data storage systems like data warehouses were designed to handle structured and preprocessed data. That’s where data lakes come in. Unlike a traditional data warehouse, which requires predefined schemas and is optimized for structured data, a data lake retains data without schema restrictions.

Data Lake 40

Data Lake Building Hadoop Raw Data 40

ProjectPro

JUNE 6, 2025

Data modeling enables the organization's departments to work together as a unit. It makes data more accessible. What does "data sparsity" imply? The number of blank cells in a database is known as data sparsity. In a data model, it describes the amount of data that is available for a specific dimension.

Data Warehouse 53

Data Warehouse NoSQL PostgreSQL Relational Database 53

ProjectPro

JUNE 6, 2025

This is the reason why we need Data Warehouses. What is Snowflake Data Warehouse? A Data Warehouse is a central information repository that enables Data Analytics and Business Intelligence (BI) activities. Snowflake Data Marketplace gives users rapid access to various third-party data sources.

Architecture 56

Architecture IT Data Warehouse Amazon Web Services 56

ProjectPro

JUNE 6, 2025

It is like a central location where quality data from multiple databases are stored. Data warehouses typically function based on OLAP (Online Analytical Processing) and contain structured and semi-structured data from transactional systems, operational databases, and other data sources.

Data Warehouse 40

Data Warehouse Data Mining Google Cloud PostgreSQL 40

ProjectPro

JUNE 6, 2025

Store processed data in Redshift for advanced querying and create visual dashboards using Tableau or Power BI to highlight trends in customer sentiment, identify frequently mentioned product features, and pinpoint seasonal buying patterns. Use the ESPNcricinfo Ball-by-Ball Dataset to process match data. venues or weather).

Data Engineering 59

Data Engineering Data Engineer Project Engineering 59

Knowledge Hut

OCTOBER 30, 2023

Ever wondered why Power BI developers are widely sought after by businesses all around the world? For any organization to grow, it requires business intelligence reports and data to offer insights to aid in decision-making. This data and reports are generated and developed by Power BI developers.

BI 52

BI Data Cleanse Business Intelligence Business Analyst 52

ProjectPro

JUNE 6, 2025

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. What is a Big Data Pipeline?

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. This ensures that companies' data is always protected and secure.

AWS 40

AWS Data Management ETL Tools Management 40

Knowledge Hut

SEPTEMBER 26, 2023

In this post, we will discuss the top power BI developer skills required to access Microsoft’s power business intelligence software. Top 10 Essential Power BI Skills Let us look at the Power BI skills list required to be a competent Business Insight Professional. Let us look at each of these elements individually.

BI 52

BI Business Intelligence Raw Data Certification 52

ProjectPro

JANUARY 27, 2023

Whether you are a data engineer, BI engineer, data analyst, or an ETL developer, understanding various ETL use cases and applications can help you make the most of your data by unleashing the power and capabilities of ETL in your organization. You have probably heard the saying, "data is the new oil".

BI 52

BI ETL Tools Retail Healthcare 52

ProjectPro

JUNE 6, 2025

Engineers perform additional tasks to alter the extracted data to comply with the format specifications (e.g., Data transformation is a crucial task since it greatly enhances the usefulness and accessibility of data. Engineers use various BI tools (dashboards, pie charts, bar graphs, etc.).

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. Data Analysts require good knowledge of Mathematics and Statistics, Coding, and Machine Learning.

Data Science 97

Data Science BI Data Mining Business Intelligence 97

ProjectPro

JUNE 6, 2025

Big Data Engineer Salary by Skills The roles and responsibilities of a Big Data Engineer in an organization vary as per the business domain, type of the project, specific big data tools in use, IT infrastructure, technology stack, and a lot more. What does a big data engineer do?

Big Data 40

Big Data Data Engineering Data Engineer Engineering 40

Snowflake

MARCH 30, 2023

The timestamp of that business object’s state is what in Data Vault is referred to as the applied date timestamp, and as data is landed to be ingested into raw vault, a load date timestamp is also recorded per record to denote when that record enters the Data Vault. Enter Snowpark !

Engineering 105

Engineering Raw Data Scala Data Science 105

ProjectPro

JUNE 6, 2025

Independent, Isolated Data Processing Resources: Independence and isolation of data processing resources within the pipeline ensure resilience and reliability, minimizing the risk of failures or disruptions and preserving data integrity and operational stability.

Data Science 40

Data Science Building Data Lake AWS 40

Cloudera

JUNE 3, 2022

When it comes to the early stages in the data science process, data scientists often find themselves jumping between a wide range of tooling. First of all, there’s the question of what data is currently available within their organization, where it is, and how it can be accessed. Next Steps.

Data Analysis 92

Data Analysis PostgreSQL Data Science Machine Learning 92

ProjectPro

JUNE 6, 2025

The advantage of gaining access to data from any device with the help of the internet has become possible because of cloud computing. It has brought access to various vital documents to the users’ fingertips. Hop on to the next section to learn more about a data engineer's responsibilities.

Data Engineering 49

Data Engineering Data Engineer Engineering Hadoop 49

ProjectPro

JUNE 6, 2025

ETL developers are also responsible for addressing data inconsistencies and performance tuning to optimize the transfer process, which plays a key role in ensuring accurate and timely access to information. On the other hand, a data engineer has a broader focus that extends beyond the ETL process.

Data Engineering 40

Data Engineering Data Engineer Engineering ETL Tools 40

ProjectPro

JUNE 6, 2025

By the end of 2022, the industry will experience a huge demand for data analysts, data scientists, and BI professionals with decent Tableau knowledge. Around 90% of companies rely on data visualizations produced using Tableau. . · · Tableau also provides a data blending facility.

BI 40

BI Database-centric SQL Software Engineer 40

ProjectPro

JUNE 6, 2025

It provides various tools and additional resources to make machine learning (ML) more accessible and easier to use, even for beginners. Amazon Transcribe Amazon Transcribe converts spoken language into written text, making audio and video content accessible for analysis and search.

Machine Learning 40

Machine Learning AWS Amazon Web Services Deep Learning 40

ProjectPro

JUNE 6, 2025

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data. Adopt Data Mesh to Power the New Wave of AI Data is evolving from a valuable asset to being treated as a product.

Cloud 105

Cloud Unstructured Data Metadata Government 105

ProjectPro

JUNE 6, 2025

show_tools_calls = True, markdown = True, ) Create a Financial Analysis Agent This agent integrates with yfinance to fetch detailed stock data such as analyst recommendations, stock prices, fundamentals, and company news: financial_agent = Agent( name="FinancialAgent", role="Fetch financial details about stocks.",

Building 40

Building Data Workflow Python Data Pipeline 40

ProjectPro

JUNE 6, 2025

Professionals aspiring to earn high-paid big data jobs must have a look at these top 6 big data companies to work for in 2015: 1) InsightSquared, Cambridge, MA InsightSquared a big data analytics company experiencing triple digit annual growth in revenues, employees and customers.

Big Data 40

Big Data Hadoop Business Analyst Data Analytics 40

Towards Data Science

JULY 21, 2023

Before you can model the data for your stakeholders, you need a place to collect and store it. However, this won’t simply be where you store your data — it’s also the power to activate it. Traditionally, transformation was a manual process, requiring data engineers to hard-code each pipeline by hand within a CLI.

Building 98

Building Business Intelligence BI Cloud Storage 98

ProjectPro

JUNE 6, 2025

Transform unstructured data into structured data by fixing errors, redundancies, missing numbers, and other anomalies, eliminating unnecessary data, optimizing data systems, and finding relevant insights. You must know how to customize reports, make reports for business users, use queries to analyze the data, etc.

NoSQL 40

NoSQL ETL Tools Certification SQL 40

Monte Carlo

JULY 19, 2023

Before you can model the data for your stakeholders, you need a place to collect and store it. Traditionally, transformation was a manual process, requiring data engineers to hard-code each pipeline by hand within a CLI. Recently, however, cloud transformation tools have begun to democratize the data modeling process.

Building 96

Building Business Intelligence Cloud Storage BI 96

ProjectPro

JUNE 6, 2025

It is useful to learn about the different cloud services AWS offers for the first-ever step of any data analytics process, i.e., data engineering on AWS! Its free tiers include access to the AWS Console, enabling users to manage their services from a single location. It allows users to easily access data from any location.

AWS 40

AWS Data Engineering Data Engineer Engineering 40

Snowflake

AUGUST 14, 2024

Cortex Analyst, built using Meta’s Llama and Mistral models, is a fully managed service that provides a conversational interface to interact with structured data in Snowflake. Historically, business users have primarily relied on BI dashboards and reports to answer their data questions.

BI 52

BI Government Analytics Application SQL 52

ProjectPro

JUNE 6, 2025

With BigQuery, users can process and analyze petabytes of data in seconds and get insights from their data quickly and easily. Moreover, BigQuery offers a variety of features to help users quickly analyze and visualize their data. It provides powerful query capabilities for running SQL queries to access and analyze data.

Bytes 40

Bytes Google Cloud Data Warehouse Cloud Storage 40

Knowledge Hut

JUNE 28, 2023

The answer lies in the strategic utilization of business intelligence for data mining (BI). Data Mining vs Business Intelligence Table In the realm of data-driven decision-making, two prominent approaches, Data Mining vs Business Intelligence (BI), play significant roles.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

ProjectPro

JUNE 6, 2025

Pandas Pandas is a popular Python data manipulation library often used for data extraction and transformation in ETL processes. It provides data structures and functions for working with structured data, making it an excellent choice for data preprocessing. Pay attention to data security and privacy.

Python 40

Python ETL Tools Data Warehouse Programming Language 40