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. Looker, PowerBI, Tableau, ThoughtSpot, …) and data pipelines tools.

Data Engineering 83

Data Engineering Data Engineer Engineering Data Lake 83

Monte Carlo

JANUARY 16, 2024

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. Easier to stream real-time data 3. Zero-copy data sharing 4.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 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

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

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 67

Metadata Data Governance Relational Database Government 67

Monte Carlo

JANUARY 12, 2024

On the data lake side, Databricks has launched Unity Catalog to help bring more metadata, structure, and governance to data assets. Real-time data/insights Being able to access real-time data for analysis might sound like overkill to some, but that’s just no longer the case.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

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

AltexSoft

MARCH 14, 2023

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59

IT Data Warehouse Data Governance Data Lake 59

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. This language is used to interact with databases and perform data manipulations and querying.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 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 Google Cloud 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 Data Lake 52

Knowledge Hut

OCTOBER 4, 2023

Power BI is a popular and widely used business intelligence tool in the data world. A report from Microsoft has manifested that around 50,000 companies have been using Power BI to clean, model, transform and visualize their data. You can identify the issues in data quality before you begin to generate reports.

BI 52

BI Systems Raw Data Business Intelligence 52

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. Zero ETL is a bit of a misnomer.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 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. Structured data is modeled to be easily searchable and occupy minimal storage space.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. What about a frantic email from your CTO about “duplicate data” in a business intelligence dashboard?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Monte Carlo

FEBRUARY 7, 2023

The company of 1,600+ employees serves over 1,000 clients, and its teams churn through massive volumes of data on a daily basis. As the company scaled, Contentsquare needed to implement a quick-value solution that could help them build the foundation of a reliable data platform. Image courtesy of Contentsquare.

Data Governance 52

Data Governance Government SQL Data Lake 52

Monte Carlo

FEBRUARY 7, 2023

The company of 1,600+ employees serves over 1,000 clients, and its teams churn through massive volumes of data on a daily basis. As the company scaled, Contentsquare needed to implement a quick-value solution that could help them build the foundation of a reliable data platform. Image courtesy of Contentsquare.

Data Governance 52

Data Governance Government SQL Data Lake 52

Knowledge Hut

DECEMBER 26, 2023

Business Intelligence Business Intelligence is an intrinsic element of modern business. By referring to the following books, you will learn about various BI tools and operations like creating reports, tracking performance, managing data sources, etc.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

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 Datasets 52

Monte Carlo

JULY 30, 2020

Ask anyone in the data industry what’s hot these days and chances are “data mesh” will rise to the top of the list. But what is a data mesh and why should you build one? Fortunately, teams seeking a new lease on data need look no further than a data mesh , an architecture paradigm that’s taking the industry by storm.

IT 45

IT Data Lake Business Intelligence Data Architecture 45

phData: Data Engineering

JANUARY 3, 2022

This means it’s business-critical that companies can derive value from their data to better inform business decisions, protect their enterprise and their customers, and grow their business. Table of Contents What is Data Engineering What is Data Governance? What is Data Science?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 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

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 Engineering 98

Data Engineering Data Engineer Engineering Data 98

Monte Carlo

MARCH 24, 2023

Data corruption Like a backup hard drive or SD card that refuses to work…on a much bigger scale. Data duplication When using multiple sources, or in the process of re-running failed jobs you might end up with the same data entered more than once. But what about the permissions and policies surrounding that table?

Data Warehouse 52

Data Warehouse AWS Cloud Data Governance 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

Meltano

FEBRUARY 22, 2023

Newer data stacks take a more integration-based, modular approach to testing tools. As a result, testing tools can now work with a wide range of data tools for ETL, business intelligence, orchestration, and so on. Deciding What to Do with Test Failures But knowing what to do with test failures is hard.

Data 52

Data Transportation Data Workflow Data Lake 52

Knowledge Hut

APRIL 25, 2023

With Power BI, data engineers can easily create interactive reports and dashboards that can be accessed from anywhere, on any device. Key features: Robust data visualization capabilities Seamless integration with Microsoft tools Easy-to-use interface 2. It is one of the most liked data engineering tools of the present day.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

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. Clouds (source: Pexels ).

Cloud 43

Cloud BI Cloud Storage Business Intelligence 43

Databand.ai

DECEMBER 13, 2022

Bob also hosts The Engineering Side of Data podcast , which is dedicated to discussions around data engineering and features a variety of guests from the data engineering space. He is constantly seeking out knowledge and being excited by the challenge of learning something new in the data science space.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

AltexSoft

JULY 29, 2022

According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Hadoop 3 expanded this list with Microsoft Azure Data Lake and Aliyun Object Storage System. Snowflake: an evolving ecosystem for all types of data.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

JANUARY 31, 2022

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. They can also design and run data apps and securely share, gather, and commercialize real-time data.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Picnic Engineering

JULY 26, 2022

Data Mesh, or Hub-and-Spoke? and other reflections on building data governance. Still, it compromises by accepting multiple versions of the same truth of multiple models, and risks a weak central governance function detached from the business. The most important thing for a successful analytics strategy.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

AltexSoft

OCTOBER 8, 2021

They are applied to retrieve data from the source systems, perform transformations when necessary, and load it into a target system ( data mart , data warehouse, or data lake). So, why is data integration such a big deal? Connections to both data warehouses and data lakes are possible in any case.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

AUGUST 24, 2021

In this project, you will explore the usage of Databricks Spark on Azure with Spark SQL and build this data pipeline. Upload it to Azure Data lake storage manually. Create a Data Factory pipeline to ingest files. Also, you get a chance to explore Azure Databricks, Data Factory, and Storage services.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

NOVEMBER 30, 2021

ETL (Extract, Transform, and Load) Pipeline involves data extraction from multiple sources like transaction databases, APIs, or other business systems, transforming it, and loading it into a cloud-hosted database or a cloud data warehouse for deeper analytics and business intelligence.

Process 52

Process Data Pipeline Data Warehouse AWS 52

phData: Data Engineering

JANUARY 3, 2022

This commonly introduces: Database or Data Warehouse API/EDI Integrations ETL software Business intelligence tooling By leveraging off-the-shelf tooling, your company separates disciplines by technology. One of our customers needed the ability to export/import data between systems and create data products from this source data.

IT 52

IT AWS Software Engineer Software Engineering 52