U-Next

SEPTEMBER 7, 2022

As data generation and consumption continue to soar, Business Intelligence (BI) has become more relevant in this digital world. With the data generation of more than 2.5 quintillion bytes daily , the significance of Big Data and Data Analytics can be recognized. What Is Business Intelligence Dashboard? .

Business Intelligence 52

Business Intelligence BI Finance Raw Data 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. On the other hand, a data warehouse contains historical data that has been cleaned and arranged. . What is Data Warehouse? . Data Warehouse in DBMS: .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Christophe Blefari

JUNE 21, 2024

Snowflake was founded in 2012 around its data warehouse product, which is still its core offering, and Databricks was founded in 2013 from academia with Spark co-creator researchers, becoming Apache Spark in 2014. Databricks is focusing on simplification (serverless, auto BI 2 , improved PySpark) while evolving into a data warehouse.

Metadata 147

Metadata Data Warehouse BI Scala 147

Monte Carlo

AUGUST 23, 2024

Fact tables capture the quantitative essence of business events – sales, clicks, shipments. Together, they transform data from a source of frustration into a navigable landscape of business intelligence. Understanding these concepts is crucial in today’s data-centric world. What are Dimension Tables?

Data Warehouse 52

Data Warehouse Raw Data Datasets Business Intelligence 52

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 Datasets Aggregated Data Data Pipeline 52

Striim

SEPTEMBER 11, 2024

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Cloud Academy

JUNE 7, 2022

The data extraction process The first step of modeling and using data begins with extracting it from different sources and putting it in a library where it can be assessed: the Data Warehouse. This data is pulled directly by end users through SQL queries or through Business Intelligence tools.

Cloud 52

Cloud Data Warehouse Raw Data Business Intelligence 52

Data Engineering Podcast

DECEMBER 11, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

Data Warehouse 100

Data Warehouse Raw Data Data Lake BI 100

Monte Carlo

FEBRUARY 15, 2023

Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute. What is a data warehouse?

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Knowledge Hut

JANUARY 18, 2024

For more information, check out the best Data Science certification. A data scientist’s job description focuses on the following – Automating the collection process and identifying the valuable data. BI developers must use cloud-based platforms to design, prototype, and manage complex data.

Data Science 98

Data Science Business Analyst Data Architect ETL Method 98

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape. Read More: What is ETL?

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Grouparoo

AUGUST 3, 2021

The mission of many data teams is a very simple one. They seek to use data to help the business take smarter actions. The input is raw data from everywhere that touches the business. How can we best get the data into a usable form? Transform : The raw data is often not enough to be useful.

Raw Data 52

Raw Data Data Warehouse SQL Coding 52

Snowflake

FEBRUARY 21, 2023

There’s no need for ETLs, pre-aggregations that sacrifice flexibility, or additional infrastructure that requires data engineering resources. Metrics API: It provides a Metrics API that not only gives meaning to your raw data but also empowers your dev teams across the company to build with a self-service analytics API.

AWS 124

AWS Building Raw Data Architecture 124

Edureka

AUGUST 29, 2024

In this respect, the purpose of the blog is to explain what is a data engineer , describe their duties to know the context that uses data, and explain why the role of a data engineer is central. What Does a Data Engineer Do? Create Business Reports: Formulate reports that will be helpful in deciding company advisors.

Data Engineer 40

Data Engineer Data Engineering Engineering Generalist 40

Hepta Analytics

FEBRUARY 14, 2022

This week, we got to think about our data ingestion design. We looked at the following: How do we ingest – ETL vs ELT Where do we store the data – Data lake vs data warehouse Which tool to we use to ingest – cronjob vs workflow engine NOTE : This weeks task requires good internet speed and good compute.

Data Ingestion 52

Data Ingestion Data Engineer Data Engineering Engineering 52

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Raw Data 69

Raw Data Data Business Intelligence Data Engineer 69

Snowflake

APRIL 5, 2023

Two different data modeling approaches—dimensional data modeling and Data Vault—each have their own pros and cons. Modernizing a data warehouse with Snowflake Data Cloud is a smart investment that can provide significant benefits to businesses of all sizes, today more than ever as data models become ever more complex.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer in the Data Science team is responsible for this sort of data manipulation. Big Data is a part of this umbrella term, which encompasses Data Warehousing and Business Intelligence as well. A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

U-Next

MARCH 7, 2023

Taking data from sources and storing or processing it is known as data extraction. Define Data Wrangling The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed.

Data Mining 96

Data Mining Scala Government Data Governance 96

Knowledge Hut

OCTOBER 30, 2023

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. The work of a Power BI developer is to take data in its raw form, derive meaning, and make sense of it.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Knowledge Hut

JUNE 30, 2023

The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. You can pace your learning by joining data engineering courses such as the Bootcamp Data Engineer.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

Data Warehouse 95

Data Warehouse Kafka Lambda Architecture Telecommunication 95

Maxime Beauchemin

AUGUST 28, 2017

Consensus seeking Whether you think that old-school data warehousing concepts are fading or not, the quest to achieve conformed dimensions and conformed metrics is as relevant as it ever was. The data warehouse needs to reflect the business, and the business should have clarity on how it thinks about analytics.

Data Engineer 174

Data Engineer Data Engineering Engineering Software Engineer 174

ProjectPro

JANUARY 27, 2023

You have probably heard the saying, "data is the new oil". It is extremely important for businesses to process data correctly since the volume and complexity of raw data are rapidly growing. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 52

BI ETL Tools Retail Healthcare 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Source : Fundamentals of Data Engineering by Joe Reis and Matt Housley. There are trade-offs.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

AltexSoft

DECEMBER 23, 2022

It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a data lake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.

Process 52

Process Building Raw Data Data Lake 52

Monte Carlo

APRIL 24, 2023

While we won’t get into the minutia of every consideration for every level of the data stack, it’s important to recall these five considerations as they’ll nonetheless steer the direction of our conversation. Data ingestion When we think about the flow of data in a pipeline, data ingestion is where the data first enters our platform.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Grouparoo

JANUARY 26, 2022

Warehouse Storage Needs The foundation of Maslow’s hierarchy of needs is about physiological needs like having enough food, water, and sleep. In the world of the modern data stack, the parallel is having a data warehouse that can act as a foundation for the work to be done. It can certainly be quite challenging.

Data Warehouse 52

Data Warehouse Food ETL Tools Raw Data 52

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

SEPTEMBER 28, 2023

It stands as a formidable business intelligence tool, providing an end-to-end solution for diverse data needs. This versatile tool handles data extraction, transformation, presentation, and sharing while granting you full control over the information you disseminate.

BI 52

BI Business Intelligence Certification Raw Data 52

Edureka

JUNE 1, 2023

Data Analytics tools and technologies offer opportunities and challenges for analyzing data efficiently so you can better understand customer preferences, gain a competitive advantage in the marketplace, and grow your business. What is Data Analytics?

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52