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. Once you sign up and create an alert in Datafold for your company data, they will send you a cool water flask.

Business Intelligence 100

Business Intelligence Data Warehouse Hadoop Data Pipeline 100

Knowledge Hut

APRIL 23, 2024

Two popular approaches that have emerged in recent years are data warehouse and big data. While both deal with large datasets, but when it comes to data warehouse vs big data, they have different focuses and offer distinct advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

APRIL 25, 2024

However, with Business intelligence dashboards, knowledge is dispersed throughout the organization, enabling users to produce interactive reports, utilize data visualization, and disseminate the knowledge with internal and external stakeholders. What is a Business Intelligence Dashboard?

Business Intelligence 52

Business Intelligence BI Raw Data Data Warehouse 52

Data Engineering Podcast

JUNE 11, 2021

In this episode Lak Lakshmanan enumerates the variety of services that are available for building your various data processing and analytical systems. He shares some of the common patterns for building pipelines to power business intelligence dashboards, machine learning applications, and data warehouses.

Google Cloud 100

Google Cloud Cloud Big Data Ecosystem Data Warehouse 100

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 Data Validation 52

Data Engineering Podcast

NOVEMBER 16, 2020

Summary The core mission of data engineers is to provide the business with a way to ask and answer questions of their data. This often takes the form of business intelligence dashboards, machine learning models, or APIs on top of a cleaned and curated data set.

Data Management 100

Data Management Management BI Business Intelligence 100

Towards Data Science

DECEMBER 4, 2023

A robust data infrastructure is a must-have to compete in the F1 business. We’ll build a data architecture to support our racing team starting from the three canonical layers : Data Lake, Data Warehouse, and Data Mart. Data Marts There is a thin line between Data Warehouses and Data Marts.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Lake 98

Data Engineering Podcast

JUNE 5, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Data teams are increasingly under pressure to deliver.

Data Security 100

Data Security Metadata MongoDB MySQL 100

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

Knowledge Hut

JANUARY 24, 2024

Power BI takes advantage of Microsoft's business analytics. The business intelligence market has multiplied in recent years and is anticipated to do so going forward. You should be data-driven if you want to pursue your career in Business Intelligence, Analytics, or Data Science.

BI 98

BI Business Intelligence Non-relational Database Machine Learning 98

Data Engineering Podcast

JULY 10, 2022

Push information about data freshness and quality to your business intelligence, automatically scale up and down your warehouse based on usage patterns, and let the bots answer those questions in Slack so that the humans can focus on delivering real value. Tired of deploying bad data?

Metadata 100

Metadata MongoDB MySQL Machine Learning 100

U-Next

MARCH 7, 2023

Data mining, report writing, and relational databases are also part of business intelligence, which includes OLAP. Give examples of python libraries used for data analysis? Data governance describes how data is collected, stored, processed, and disposed of according to internal standards.

Data Mining 96

Data Mining Government Scala Data Governance 96

Striim

SEPTEMBER 11, 2024

The approach to this processing depends on the data pipeline architecture, specifically whether it employs ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes. This method is advantageous when dealing with structured data that requires pre-processing before storage. In what format will the final data be stored?

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Cloudera

AUGUST 21, 2024

This year, we’re excited to share that Cloudera’s Open Data Lakehouse 7.1.9 release was named a finalist under the category of Business Intelligence and Data Analytics. The root of the problem comes down to trusted data.

Unstructured Data 66

Unstructured Data Business Intelligence Data Architecture Data Warehouse 66

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

JANUARY 23, 2024

It’s harder to gain consensus on governance – and that’s OK In a previous era of data engineering, data team structure was very much centralized, with data engineers and tech-savvy analysts serving as the “librarians” of the data for the entire company. Data debt or data pipeline chaos.

Data Engineering 98

Data Engineering Data Engineer Engineering Data 98

RandomTrees

SEPTEMBER 27, 2024

A cloud-based software as a service (SaaS) called Microsoft Fabric combines several data and analytics technologies that businesses require. Data Factory, Data Activator, Power BI, Synapse Real-Time Analytics, Synapse Data Engineering, Synapse Data Science, and Synapse Data Warehouse are some of them.

Database-centric 52

Database-centric Pipeline-centric IT BI 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

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 5.

Metadata 69

Metadata Relational Database Data Governance Government 69

Cloudera

DECEMBER 2, 2020

With access to vast amounts of data from its customer base, the company knew its ability to mine this data would be a key driver of positive transformation. However, it was locked into an expensive legacy data warehouse which resulted in high operational costs and the inability to perform exploratory analytics.

Telecommunication 67

Telecommunication Data Science Business Intelligence Data Warehouse 67

Monte Carlo

AUGUST 19, 2023

To make things a little easier, I’ve outlined the six must-have layers you need to include in your data platform and the order in which many of the best teams choose to implement them. The five must-have layers of a modern data platform Second to “how do I build my data platform?”,

Building 52

Building BI Data Lake Data Governance 52

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. A power BI developer has a crucial role in business management. Ensure compliance with data protection regulations.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Machine Learning 64

Striim

NOVEMBER 15, 2023

Through Striim’s breakthrough of AI-ready data streaming, we’re ushering in a new era of analytics and AI, all harmonized under a single data platform on Microsoft Azure. All of these services are served by OneLake, a unified intelligent storage layer that solves the complex problem of decentralized data teams working in silos.

Retail 52

Retail BI Data Warehouse Business Analyst 52

Snowflake

JANUARY 23, 2023

One reason for this is that dependencies usually exist outside of the marketing team, such as marketing ops serving as a liaison, and marketing campaign teams are the “consumer” in the integration/modeling/data warehouse activities. Data models also help with data governance and legal compliance, as well as ensuring data integrity.

Data Integration 69

Data Integration Data Data Warehouse Cloud 69

Monte Carlo

JANUARY 16, 2024

At the center of it all is the data warehouse, the lynchpin of any modern data stack. In this blog post, we’ll look at six innovations that are shaping the future of the data warehousing, as well as challenges and considerations that organizations should keep in mind. Data lake and data warehouse convergence 2.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Edureka

FEBRUARY 9, 2023

Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. Data ingestion, transformation, and storage are among their responsibilities, as are data governance and security. Data Modeling: Data modeling is the process of creating a conceptual representation of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

phData: Data Engineering

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Monte Carlo

JUNE 7, 2024

This week at their annual summit, Snowflake announced Horizons, a new data governance suite that helps teams achieve data discovery, compliance, and quality in Snowflake. As the Snowflake Horizon data observability partner , we are excited to see this initiative deliver value to our mutual customers.

Business Intelligence 40

Business Intelligence Kafka Data Warehouse Data Governance 40

Edureka

AUGUST 28, 2024

As the world becomes more and more dependent on data, it becomes increasingly important to be able to make sense of Business Intelligence. Meet Looker, a promising business intelligence (BI) platform that is revolutionizing the way companies engage with data. What is a looker?

BI 40

BI Data Analysis Business Intelligence Google Cloud 40

Monte Carlo

SEPTEMBER 1, 2022

Speaking of decentralizing… Leverage decentralized “data meshy” team structures There are a number of factors that will determine if a data mesh model is right for your team including organizational structure, business workflow maturity, and data product use cases. It’s human nature to gravitate toward the known.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Many of us are all too familiar with the traditional way enterprises operate when it comes to on-premises data warehousing and data marts: the enterprise data warehouse (EDW) is often the center of the universe.

Cloud 43

Cloud BI Cloud Storage Business Intelligence 43

Monte Carlo

MARCH 28, 2023

For example, the marketing team may require their ad spend dashboard updated weekly for their regular meeting where they make optimization decisions, but a machine learning algorithm that detects financial fraud may require data latency measured in seconds (or less).

IT 52

IT Machine Learning Data Business Intelligence 52

ProjectPro

JANUARY 27, 2023

Top ETL Business Use Cases for Streamlining Data Management Data Quality - ETL tools can be used for data cleansing, validation, enriching, and standardization before loading the data into a destination like a data lake or data warehouse.

BI 52

BI ETL Tools Retail Healthcare 52

phData: Data Engineering

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52