Cloudera

DECEMBER 2, 2020

With more than 25TB ingested from over 200+ different data sources, Telkomsel knew an agile and cost-efficient infrastructure was key to pursuing a digital-first strategy. . To kick start its mission to become a digital telco company, it turned to Cloudera to enable more cost-effective data storage.

Telecommunication 67

Telecommunication Data Science Business Intelligence Data Warehouse 67

AltexSoft

MARCH 14, 2023

Batch jobs are often scheduled to load data into the warehouse, while real-time data processing can be achieved using solutions like Apache Kafka and Snowpipe by Snowflake to stream data directly into the cloud warehouse. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? 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

Sync Computing

NOVEMBER 7, 2024

A brief history of data storage The value of data has been apparent for as long as people have been writing things down. Data volume and velocity, governance, structure, and regulatory requirements have all evolved and continue to. In a data lake raw data can be stored and accessed directly.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

phData: Data Engineering

SEPTEMBER 19, 2023

This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake? What are Data Modeling Methodologies, and Why Are They Important for a Data Lake? Contact phData Today!

Data Lake 52

Data Lake Process Metadata Data Warehouse 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

AltexSoft

SEPTEMBER 23, 2021

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Knowledge Hut

APRIL 23, 2024

Data Warehousing A data warehouse is a centralized repository that stores structured historical data from various sources within an organization. It is designed to support business intelligence (BI) and reporting activities, providing a consolidated and consistent view of enterprise data.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

JANUARY 12, 2024

Beyond that, a data observability platform like Monte Carlo can automate monitoring, alerting, lineage, and triaging to highlight data quality and discoverability issues (and potential issues). The ultimate goal here is to eliminate bad data altogether and prevent it from recurring.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

Knowledge Hut

DECEMBER 7, 2023

Parameters Power BI DevOps Functionalities Business intelligence. Data handling capacity Power BI uses columnar data storage, which allows for up to 10X compression Data backups, data migrations, and database schema Cost effectiveness Starts from $2 per GB Starts from $9.99

BI 52

BI Business Intelligence Datasets Data Analysis 52

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

Monte Carlo

JUNE 2, 2024

Data Infrastructure Engineers also implement governance and quality frameworks to maintain data integrity and consistency. They set up redundancy and backup solutions to protect against data loss, ensuring data is always ready for business intelligence and analytics.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Monte Carlo

JUNE 2, 2024

Data Infrastructure Engineers also implement governance and quality frameworks to maintain data integrity and consistency. They set up redundancy and backup solutions to protect against data loss, ensuring data is always ready for business intelligence and analytics.

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

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 Engineer 52

Data Engineer Data Engineering Engineering Data Governance 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? The tissue connecting these domains and their associated data assets is a universal interoperability layer that applies the same syntax and data standards.

IT 45

IT Data Lake Architecture Data Architecture 45

Knowledge Hut

JUNE 23, 2023

You must develop predictive models to help industries and businesses make data-driven decisions. Steps to Become a Data Engineer One excellent point is that you don’t need to enter the industry as a data engineer. Step 3 - How to Choose Project Management Courses for Data Engineer Learning Path?

Data Engineer 52

Data Engineer Data Engineering Engineering NoSQL 52

Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. 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

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 Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 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. Find sources of relevant data. Choose data collection methods and tools.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? This is frequently referred to as a 5 or 7 layer (depending on who you ask) data stack like in the image below. Here are some of the most common solutions that are involved in modern data pipelines and the role they play.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Knowledge Hut

SEPTEMBER 6, 2023

They highlight competence in data management, a pivotal requirement in today's business landscape, making certified individuals a sought-after asset for employers aiming to efficiently handle, safeguard, and optimize data operations. Skills acquired : Core data concepts. Data storage options.

Certification 52

Certification Database MongoDB MySQL 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

phData: Data Engineering

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications. This noticeably saves time on copying and drastically reduces data storage costs.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Monte Carlo

APRIL 20, 2023

Overwhelmed data engineers need to have the proper context of the blast radius to understand which incidents need to be addressed right away, and which incidents are a secondary priority. This is one of the most frequent data lineage use cases leveraged by Vox.

Data Warehouse 52

Data Warehouse BI Data Government 52

AltexSoft

JULY 29, 2022

Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Definitely, not.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Edureka

APRIL 15, 2025

making sensible use of repartition()) Caching or indexing data that is frequently accessed Making SQL or Spark queries more efficient to prevent bottlenecks Implementing Logging and Alerting Mechanisms Error detection must be proactive. Data Warehousing : Focus on partitioning, storage optimization, and managing warehouses efficiently.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Ingestion 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 Warehouse Data Pipeline AWS 52