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

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.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Striim

JANUARY 4, 2023

Companies need to analyze large volumes of datasets, leading to an increase in data producers and consumers within their IT infrastructures. These companies collect data from production applications and B2B SaaS tools (e.g., This data makes its way into a data repository, like a data warehouse (e.g.,

PostgreSQL 52

PostgreSQL Data Warehouse Data Lake Data 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 Engineering Data engineering is a process by which data engineers make data useful.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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 89

Data Lake Data Warehouse Cloud Unstructured Data 89

Rockset

AUGUST 2, 2023

The steps Windward takes to create proprietary data and AI insights As Windward operated in a batch-based data stack, they stored raw data in S3. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Cloudera

MAY 17, 2021

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Data Warehouse 88

Data Warehouse Cloud Government Metadata 88

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

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. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

MARCH 14, 2023

Discovering the data mesh BlaBlaCar’s data stack was built to support their end goal of supporting self service analytics at scale. BlaBlaCar has been a data-driven company for a long time. In an effective data mesh, data governance tools need to be standardized,” said Kineret. Image courtesy of BlaBlaCar.

Transportation 40

Transportation Government Google Cloud Architecture 40

Monte Carlo

JANUARY 25, 2023

In an evolving data landscape, the explosion of new tooling solutions—from cloud-based transforms to data observability —has made the question of “build versus buy” increasingly important for data leaders. Data storage and compute are very much the foundation of your data platform. Let’s jump in!

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Data Engineering Podcast

JUNE 17, 2021

In this episode he shares the goals of the Unstruk Data Warehouse, how it is architected to extract asset metadata and build a searchable knowledge graph from the information, and the myriad ways that the system can be used. Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

Monte Carlo

FEBRUARY 26, 2024

A data catalog is a constantly updated inventory of the universe of data assets within an organization. It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems.

Metadata 52

Metadata Government Data Data Governance 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

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. With cost and physical compute/storage limitations largely lifted, data engineers started to optimize data pipeline architecture for speed and agility.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Towards Data Science

MARCH 5, 2024

At its core, BigQuery is a serverless Data Warehouse for analytical purposes and built-in features like Machine Learning ( BigQuery ML ). The storage system is using Capacitor, a proprietary columnar storage format by Google for semi-structured data and the file system underneath is Colossus, the distributed file system by Google.

Bytes 72

Bytes Google Cloud Cloud Storage Utilities 72

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

AUGUST 22, 2022

According to Flexera’s 2022 State of the Cloud Report , 89 percent of respondents have a multi-cloud strategy with 80 percent having a hybrid cloud approach in place. Organizations have data stored in public and private clouds, as well as in various on-premises data repositories. Source: Flexera.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Note, though, that not any type of web scraping is legal.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

OCTOBER 8, 2021

Data integration defines the process of collecting data from a number of disparate source systems and presenting it in a unified form within a centralized location like a data warehouse. So, why is data integration such a big deal? On-premise data integration tools. Cloud-based data integration tools.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.

Engineering 82

Engineering Raw Data Data Science Scala 82

ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

AltexSoft

JULY 29, 2022

How HDFS master-slave structure works. A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. Today, companies have the opportunity to run Big Data analytics on Hadoop without investing in hardware.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

NOVEMBER 15, 2021

As per the surveyors, Big data (35 percent), Cloud computing (39 percent), operating systems (33 percent), and the Internet of Things (31 percent) are all expected to be impacted by open source shortly. Following these statistics, big data is set to get bigger with the evolution of open-source projects.

Big Data 52

Big Data Project Metadata Programming Language 52

Ascend.io

JUNE 8, 2023

Acting as the core infrastructure, data pipelines include the crucial steps of data ingestion, transformation, and sharing. Data Ingestion Data in today’s businesses come from an array of sources, including various clouds, APIs, warehouses, and applications.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Netflix Tech

DECEMBER 14, 2018

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

Media 94

Media Database Metadata Data Schemas 94

AltexSoft

JULY 27, 2021

Content-based systems largely depend on the metadata of items. The choice of storage depends on the type of data you’re going to use for recommendations in the first place. Or you may use a mix of different data repositories depending on the purposes. Users get limited to items similar to those they have previously consumed.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

Towards Data Science

DECEMBER 23, 2023

Photo by Ian Taylor on Unsplash This tutorial guides you through an analytics use case, analyzing semi-structured data with Spark SQL. We’ll start with the data engineering process, pulling data from an API and finally loading the transformed data into a data lake (represented by MinIO ).

SQL 75

SQL Data Analytics Hadoop Raw Data 75

ProjectPro

JANUARY 31, 2023

Data Variety Hadoop stores structured, semi-structured and unstructured data. RDBMS stores structured data. Data storage Hadoop stores large data sets. RDBMS stores the average amount of data. Map tasks deal with mapping and data splitting, whereas Reduce tasks shuffle and reduce data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

APRIL 26, 2016

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Language It is a procedural data flow language. Hcatalog can be used to share data structures with external systems.

Hadoop 40

Hadoop Metadata SQL Database 40

ProjectPro

OCTOBER 20, 2021

The orchestration of pipelines can happen on various platforms but are generally integrated with cloud providers such as Microsoft Azure, Amazon Web Services , or Google Cloud Platform at an Enterprise Level. AI Interview Questions and Answers on AI Cloud Services 6) What is an API? 8) What Cloud Service would you prefer?

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

JUNE 23, 2016

Thus, this solution is not practically recommended and this is when Apache Sqoop comes to the rescues of users that allows users to import data on HDFS. Apache Sqoop is a lifesaver for people facing challenges with moving data out of a data warehouse into the Hadoop environment. Data import in sqoop is not event driven.

Hadoop 40

Hadoop MySQL Relational Database Java 40

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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

Cloudera

APRIL 1, 2024

We’re excited to share that Gartner has recognized Cloudera as a Visionary among all vendors evaluated in the 2023 Gartner® Magic Quadrant for Cloud Database Management Systems. Download the complimentary 2023 Gartner Magic Quadrant for Cloud Database Management Systems report.

Cloud 101

Cloud Unstructured Data Metadata Datasets 101