Edureka

SEPTEMBER 11, 2023

Today’s business world is very complex and always changing, so businesses have to be able to respond quickly to changes in technology, consumer behaviour, and market conditions. The huge amount of data created every second is one of the main reasons for this complexity. Table of Contents What is business intelligence (BI)?

Business Intelligence 52

Business Intelligence BI Database-centric Raw Data 52

Edureka

FEBRUARY 27, 2023

Business Intelligence Trends: Business intelligence (BI) is becoming an ever more critical element in the success of a business. We’ll also look into ways that businesses can successfully incorporate BI into their practices to gain competitive advantages. What is Business Intelligence?

Business Intelligence 52

Business Intelligence BI Data Mining Data Warehouse 52

Monte Carlo

FEBRUARY 6, 2023

So, you’re planning a cloud data warehouse migration. But be warned, a warehouse migration isn’t for the faint of heart. As you probably already know if you’re reading this, a data warehouse migration is the process of moving data from one warehouse to another. A worthy quest to be sure.

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

U-Next

SEPTEMBER 7, 2022

The terms “ Data Warehouse ” and “ Data Lake ” may have confused you, and you have some questions. Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. What is Data Warehouse? .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Monte Carlo

AUGUST 25, 2023

Modern companies are ingesting, storing, transforming, and leveraging more data to drive more decision-making than ever before. At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Podcast

FEBRUARY 5, 2023

In that time there have been a number of generational shifts in how data engineering is done. Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? Materialize]([link] Looking for the simplest way to get the freshest data possible to your teams?

Data Engineering 147

Data Engineering Data Engineer Engineering PostgreSQL 147

Cloudera

MARCH 2, 2022

Apache Impala is used today by over 1,000 customers to power their analytics in on premise as well as cloud-based deployments. Similarly, with better usage of available memory more users can query the data at any given time, so more people can use the warehouse at the same time. Folding data into pointers.

Data Warehouse 88

Data Warehouse Bytes Data Business Intelligence 88

Data Engineering Podcast

JUNE 11, 2021

Summary Google pioneered an impressive number of the architectural underpinnings of the broader big data ecosystem. Now they offer the technologies that they run internally to external users of their cloud platform. Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads?

Google Cloud 100

Google Cloud Cloud Big Data Ecosystem BI 100

Data Engineering Weekly

MAY 26, 2024

link] Meta: Composable data management at Meta Meta writes about its transition to a composable data management system to improve interoperability, reusability, and engineering efficiency. seconds, enhancing real-time sports data analytics efficiency! The author highlights some of the key missing features from S3.

Data Engineering 57

Data Engineering Data Engineer Engineering Google Cloud 57

Cloud Academy

JUNE 7, 2022

How Do We Transform and Model Data at Cloud Academy? “Data is the new gold”: a common phrase over the last few years. For all organizations, data and information have become crucial to making good decisions for the future and having a clear understanding of how they’re making progress — or otherwise.

Cloud 52

Cloud Data Warehouse Raw Data Business Intelligence 52

Data Engineering Podcast

JANUARY 15, 2023

Summary The modern data stack has made it more economical to use enterprise grade technologies to power analytics at organizations of every scale. At the Modern Data Company they created the DataOS platform as a means of driving your full analytics lifecycle through code, while providing automatic knowledge graphs and data discovery.

Coding 130

Coding Building PostgreSQL Data Lake 130

Data Engineering Podcast

JANUARY 8, 2023

Summary Managing end-to-end data flows becomes complex and unwieldy as the scale of data and its variety of applications in an organization grows. Part of this complexity is due to the transformation and orchestration of data living in disparate systems. Missing data? Start trusting your data with Monte Carlo today!

PostgreSQL 130

PostgreSQL Data Lake Data Warehouse BI 130

Cloud Academy

NOVEMBER 6, 2022

At Cloud Academy , we manage a lot of data every day. We have different sources we get data from such as feedback, events, and platform usage, and we need to get it, apply transformations, and finally present the data to our internal stakeholders and our customers. What is a Headless BI Tool?

Cloud 52

Cloud BI Data Warehouse Business Intelligence 52

Data Engineering Podcast

DECEMBER 18, 2022

Summary One of the reasons that data work is so challenging is because no single person or team owns the entire process. This introduces friction in the process of collecting, processing, and using data. In order to reduce the potential for broken pipelines some teams have started to adopt the idea of data contracts.

Metadata 130

Metadata Business Intelligence Data Lake BI 130

Data Engineering Podcast

SEPTEMBER 29, 2021

Summary The promise of online services is that they will make your life easier in exchange for collecting data about you. There have been many attempts to harness all of the data that you generate for gaining useful insights about yourself, but they are generally difficult to set up and manage or require software development experience.

Cloud 100

Cloud Data Lake Business Intelligence Data 100

Advancing Analytics: Data Engineering

JULY 2, 2019

The data engineer is an emerging role that’s rapidly growing in popularity… but what is it? But I don’t agree; I think there was a very specific function that was heavily tied into data science that has evolved in the past two years into something new.

Business Intelligence 52

Business Intelligence Data Engineering Data Engineer Engineering 52

Cloudera

SEPTEMBER 9, 2018

We are proud to announce the general availability of Cloudera Altus Data Warehouse , the only cloud data warehousing service that brings the warehouse to the data. Modern data warehousing for the cloud. Cloudera Altus Data Warehouse is designed with agile data teams in mind.

Data Warehouse 40

Data Warehouse Metadata Cloud Storage Cloud 40

Edureka

JUNE 1, 2023

In today’s digital era, businesses operate in a data-driven environment where data is generated at an unprecedented rate. This is where AWS Data Analytics comes into action, providing businesses with a robust, cloud-based data platform to manage, integrate, and analyze their data.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Data Engineering Weekly

APRIL 14, 2024

Discover how a universal semantic layer is transforming modern business intelligence, making data more accessible and reliable for organizations striving for informed business decisions. Large Language Models: Turning messy data into surprisingly coherent nonsense since 2023.

Data Engineering 62

Data Engineering Data Engineer Engineering Business Intelligence 62

phData: Data Engineering

DECEMBER 20, 2022

Congratulations—at last, you’ve finished your cloud data migration and it feels as if you just bought a brand new car! Hopefully, your cutting-edge cloud data warehouse comes with the latest and greatest safety features, too. Why Do Businesses Invest in Cloud Data Migrations?

Cloud 52

Cloud Database-centric Data Data Warehouse 52

Towards Data Science

NOVEMBER 4, 2023

Platform Specific Tools and Advanced Techniques Photo by Christopher Burns on Unsplash The modern data ecosystem keeps evolving and new data tools emerge now and then. In this article, I want to talk about crucial things that affect data engineers. Are your data pipelines efficient? Data warehouse exmaple.

Data Engineering 83

Data Engineering Data Engineer Engineering BI 83

Monte Carlo

JANUARY 23, 2024

In the world of data engineering, Maxime Beauchemin is someone who needs no introduction. One of the first data engineers at Facebook and Airbnb, he wrote and open sourced the wildly popular orchestrator, Apache Airflow , followed shortly thereafter by Apache Superset , a data exploration tool that’s taking the data viz landscape by storm.

Data Engineering 98

Data Engineering Data Engineer Engineering Data 98

Data Engineering Podcast

NOVEMBER 4, 2021

Summary The precursor to widespread adoption of cloud data warehouses was the creation of customer data platforms. Acting as a centralized repository of information about how your customers interact with your organization they drove a wave of analytics about how to improve products based on actual usage data.

Data Warehouse 100

Data Warehouse Business Intelligence ETL System Data Lake 100

Data Engineering Podcast

APRIL 26, 2021

Summary The reason for collecting, cleaning, and organizing data is to make it usable by the organization. One of the most common and widely used methods of access is through a business intelligence dashboard. Modern Data teams are dealing with a lot of complexity in their data pipelines and analytical code.

Business Intelligence 100

Business Intelligence Data Warehouse Hadoop Data Pipeline 100

Monte Carlo

JULY 19, 2023

Building a data stack doesn’t have to be complicated. Here’s what data leaders say are the 5 must-have layers of your data platform to drive data adoption – and ROI – across your business. Like bean dip and ogres , layers are the building blocks of the modern data stack.

Building 96

Building Business Intelligence Cloud Storage BI 96

Knowledge Hut

DECEMBER 29, 2023

The market for analytics is flourishing, as is the usage of the phrase Data Science. Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

RandomTrees

NOVEMBER 29, 2023

The choice of tools and adopting the right methodologies becomes the drive for any business and in this the selection on the database technologies is very crucial. In this choice, Big Data will play an important role and its choice is also inevitably crucial in the Business Intelligence and related systems.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52

Data Engineering Podcast

DECEMBER 29, 2022

Summary Making effective use of data requires proper context around the information that is being used. Rehgan Avon co-founded AlignAI to help address this challenge through a more purposeful platform designed to collect and distribute the knowledge of how and why data is used in a business. Missing data?

Management 130

Management Metadata Business Intelligence Data Lake 130

Knowledge Hut

JANUARY 24, 2024

Step into the realm of data visualization with a comprehensive exploration of Power BI and Tableau. In a world where data is important, deciding between power bi vs tableau can change your path in analyzing things. Are you ready to unlock my data potential and master advanced analytics! Utilizing Power BI is simple.

BI 98

BI Business Intelligence Non-relational Database Data Analysis 98

Data Science Blog: Data Engineering

DECEMBER 23, 2022

Warum Data Engineering der Data Science in Bedeutung und Berufschancen längst die Show stiehlt, dabei selbst ebenso einem stetigen Wandel unterliegt. Was ein Data Engineer wirklich können muss Der Data Scientist als sexiest Job des 21. Data Engineer, der gefragteste Job des 21sten Jahrhunderts? Jahrhunderts?

Data Engineering 52

Data Engineering Data Engineer Engineering Business Intelligence 52

Towards Data Science

JULY 21, 2023

Spinning up a data platform doesn’t have to be complicated. Here are the 5 must-have layers to drive data product adoption at scale. Like bean dip and ogres , layers are the building blocks of the modern data stack. Unlike ogres, however, the cloud data platform isn’t a fairy tale. Image courtesy of author.

Building 80

Building Business Intelligence BI Cloud Storage 80

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

Snowflake

SEPTEMBER 7, 2023

The university needed to modernize its data capabilities to better serve staff, students and researchers—and it used the Snowflake Data Cloud to do it. Siloed departmental data with no single source of truth Without a single source of truth, version control and data management were complicated.

Education 88

Education Business Intelligence Professional Services Cloud 88

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data. Missing data?

Systems 100

Systems Building Metadata Data Warehouse 100

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Advancing Analytics: Data Engineering

JUNE 21, 2019

Ah the ETL (Extract-Transform-Load) Window, the schedule by which the Business Intelligence developer sets their clock, the nail-biting nightly period during which the on-call support hopes their phone won’t ring. It’s a cornerstone of the data warehousing approach… and we shouldn’t have one. There, I said it.

Data Warehouse 52

Data Warehouse Business Intelligence Data Data Validation 52

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Cloud 52

Cloud AWS Data Lake Amazon Web Services 52