Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Central to this transformation are two shifts.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Towards Data Science

JANUARY 16, 2024

New data formats emerged — JSON, Avro, Parquet, XML etc. Data lakes were introduced to store the new data formats. Image by the author 2010 to 2020 - The Cloud Data Warehouse Enterprises now wanted quick data analytics without yesterday’s constraints of flexibility, processing power and scale.

Data Warehouse 68

Data Warehouse Data Architecture Relational Database NoSQL 68

U-Next

MARCH 1, 2023

Let’s discuss some of the key responsibilities of a Data Engineer: Data Engineers are responsible for deploying the solutions they design and build, and they should have a good knowledge of cloud platforms like AWS, Azure, etc. What is a data lake, and how does it differ from a data warehouse?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

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. Your CTO is excited about migrating to the cloud, and constantly sends your team articles highlighting performance measurements against some of the latest technologies.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

APRIL 25, 2023

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Rockset

APRIL 26, 2023

This architecture has a few key components: Streaming data : Streaming data is generated by website activity and transported to Rockset via Confluent Cloud. Offline feature store : Detecting anomalies requires historical data in order to have a baseline for comparisons. This will significantly reduce storage costs.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Cloudera

DECEMBER 11, 2020

Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions. It established a data governance framework within its enterprise data lake. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

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 Engineering Data Engineer Engineering 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems. So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

FEBRUARY 16, 2023

Data Engineers and Data Scientists require efficient methods for managing large databases, which is why centralized data warehouses are in high demand. Cloud computing has made it easier for businesses to move their data to the cloud for better scalability, performance, solid integrations, and affordable pricing.

AWS 52

AWS Data Management ETL Tools Management 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. These patterns include both centralized storage patterns like data warehouse , data lake and data lakehouse , and distributed patterns such as data mesh.

Data Lake 92

Data Lake Data Warehouse Cloud Unstructured Data 92

Knowledge Hut

OCTOBER 5, 2023

When it comes to cloud computing and big data, Amazon Web Services (AWS) has emerged as a leading name. As businesses’ reliance on cloud and big data increases, so does the demand for professionals who have the necessary skills and knowledge in AWS.

Big Data 52

Big Data AWS Certification Amazon Web Services 52

Rockset

JULY 29, 2022

Google BigQuery BigQuery is Google’s data warehouse service and one of the first cloud data warehouses released to the public. However, the data via its streaming API insert isn’t available for two to three minutes. So, it’s not real-time data. The Snowpipe feature manages continuous data ingestion.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse. Data Integration Combining data from various, disparate sources into one unified view.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Rockset

NOVEMBER 5, 2021

Challenge 1: Scaling PostgreSQL for Analytics DataBrain was using PostgreSQL through Amazon RDS to land and query both incoming customer data as well as internal company data. This made sense when DataBrain didn’t have large amounts of data or complex queries to run. One customer was already generating 60 million rows of data.

PostgreSQL 52

PostgreSQL Structured Data Data Lake Data Ingestion 52

Snowflake

JULY 10, 2023

Processing files in a Python UDF and Stored Procedure has piqued the interest of our data scientists and paves the way for automation of new, complex data pipelines.” Mike Tuck, Air Pollution Specialist Why unstructured data? Using a Python UDF, we were able to accomplish this task.

Unstructured Data 40

Unstructured Data Python Process Scala 40

Monte Carlo

AUGUST 25, 2023

At the same time, 81% of IT leaders say their C-suite has mandated no additional spending or a reduction of cloud costs. Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. But, the options for data storage are evolving quickly.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

DECEMBER 26, 2023

Down below, we have listed some books that are widely used to learn about web scraping:- Web Scraping with Python: Collecting More Data from the Modern Web (Author: Ryan Mitchell) Getting Structured Data from the Internet: Running Web Crawlers/Scrapers on a Big Data Production Scale (Author: Jay M.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Striim

JANUARY 4, 2023

That’s because you don’t know how many target environments can be used to ingest data from your operational systems. Maybe, you first load data into a data warehouse and later go on to load data into a data lake. Cover schemas in data contracts.

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 52

Monte Carlo

SEPTEMBER 6, 2022

As a result, vendors like Databricks have moved toward allowing users to add more structure to their data via offerings like Delta Lake and Unity Catalog. As a result, vendors like Databricks have moved toward allowing users to add more structure to their data via offerings like Delta Lake and Unity Catalog.

Data Lake 52

Data Lake Machine Learning Data Science Data 52

Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Define data architecture standards and best practices.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Knowledge Hut

DECEMBER 26, 2023

Technologies like Hadoop, Spark, and NoSQL Big Data structures Data Lake A Big Data Analyst makes an average yearly pay of US$111,793 in the United States, whereas a Data Scientist makes an average yearly compensation of US$96,494.

Banking 52

Banking Insurance Finance Cloud Computing 52

Rockset

JULY 6, 2022

This radical design choice made NoSQL databases — document databases, key-value stores, column-oriented databases and graph databases — great at storing huge amounts of data of varying kinds together, whether it is structured, semi-structured or polymorphic. And when it comes to the cloud and developers, that means wasted money.

NoSQL 52

NoSQL SQL Systems PostgreSQL 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 Lake? .

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

Knowledge Hut

JANUARY 19, 2024

Data Warehousing Data warehousing is like a well-organized library for data. It centralizes data, making it easy to find. The syllabus, resembling a guidebook, talks about organized storage, a unified view, and the flexibility offered by data lakes. Importance: Efficient organization and retrieval of data.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

U-Next

OCTOBER 20, 2022

Reporting and analytics may experience a number of issues as a result of this ambiguous data. . Duplicate Data: The sources of data that modern organizations must manage include local databases, cloud data lakes, and streaming data. They might also have silos for their systems and applications.

Data Collection 52

Data Collection Big Data Data Medical 52

Rockset

JANUARY 28, 2020

Using Rockset as their prototyping platform, Standard engineers can quickly experiment with different functions on the data. Standard also uses Rockset for fast prototyping because it can be readily accessed as a fully managed cloud service. For feature prototyping, engineers build an experimental API, using the Rockset Node.js

Retail 40

Retail Google Cloud Raw Data Data Lake 40

Edureka

JUNE 1, 2023

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. In this blog, we’ll explore the world of Cloud Data Analytics and a real-life application of AWS Data Analytics. How can the Cloud Help?

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Knowledge Hut

SEPTEMBER 26, 2023

Microsoft Azure, also known as Azure, is a well-known cloud computing service offered by Microsoft. It offers a wide range of services, including computing, storage, databases, machine learning, and analytics, making it a versatile choice for businesses looking to harness the power of the cloud. What is Azure Synapse?

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

ProjectPro

SEPTEMBER 26, 2021

Demand for Big Data Engineer Jobs Data Science is becoming an essential technology for organizations due to increasing data volumes. Organizations now generate and process vast volumes of data daily. The adoption of cloud databases and technologies has further led to the expansion in data volumes.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

ProjectPro

FEBRUARY 16, 2023

Additionally, SQL enables data engineers to perform data transformation tasks like data cleaning or aggregation from various data sources and loading data into data warehouses or other storage systems using simple SQL queries. They must load the raw data into a data warehouse for this analysis.

Data Engineering 52

Data Engineering Data Engineer SQL Engineering 52

DareData

JANUARY 30, 2023

AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS). Talend Data Fabric: A comprehensive data management platform that includes a range of tools for data integration, data quality, and data governance. Introduction to Designing Data Lakes in AWS.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Monte Carlo

JUNE 14, 2023

Some organizations choose to still leverage an ETL pattern in the cloud, particularly for production pipelines where data contracts can help reduce data downtime. The term modern data stack refers to the multiple modular SaaS solutions that comprise the data platform and pipeline (more on those later).

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

AUGUST 4, 2021

Since data marts provide analytical capabilities for a restricted area of a data warehouse, they offer isolated security and isolated performance. Data mart vs data warehouse vs data lake vs OLAP cube. Data lakes, data warehouses, and data marts are all data repositories of different sizes.

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Data Lake Data Warehouse ETL Tools Telecommunication 64