Towards Data Science

MAY 3, 2023

VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. You can use VDK to build data lakes and ingest raw data extracted from different sources, including structured, semi-structured, and unstructured data.

Data Lake 87

Data Lake Data SQL Data Warehouse 87

Netflix Tech

JANUARY 25, 2023

We will cover more details on Semantic Search support in a future blog article. Semantic search Range Intersection  — We recently started supporting the range intersection queries across multiple annotation types for a specific title in the real time. We support semantic search using Open Distro for ElasticSearch .

Algorithm 113

Algorithm Media Metadata Data Ingestion 113

AltexSoft

AUGUST 29, 2023

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. This article explains what a data lake is, its architecture, and diverse use cases. Make sure to check out our dedicated article.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Metadata layer The metadata layer manages and organizes the metadata associated with the data that’s been ingested and stored.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

This architecture format consists of several key layers that are essential to helping an organization run fast analytics on structured and unstructured data. Metadata layer The metadata layer manages and organizes the metadata associated with the data that’s been ingested and stored.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Ascend.io

AUGUST 24, 2023

In recent years, the data space has transformed significantly. This article introduces you to the Data Automation Engineer — a pivotal role in today’s data-driven world. This isn’t just about processing data; it’s about crafting a tangible asset that businesses can leverage.

Engineering 52

Engineering Data Pipeline Data Ingestion Data 52

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 70

Data Warehouse Cloud Kafka Cloud Storage 70

Knowledge Hut

OCTOBER 3, 2023

Effective data utilization also plays a pivotal role in enhancing customer service, contributing to the surge in demand for professionals in this field. Within the Microsoft Azure ecosystem, the role of an Azure data engineer stands out as one of the most sought-after positions.

Data Engineering 52

Data Engineering Data Engineer Engineering Cloud Computing 52

Knowledge Hut

JULY 27, 2023

The interesting world of big data and its effect on wage patterns, particularly in the field of Hadoop development, will be covered in this guide. To ensure effective data processing and analytics for enterprises, work with data analysts, data scientists, and other stakeholders to optimize data storage and retrieval.

Hadoop 52

Hadoop Programming Language Banking Scala 52

Knowledge Hut

DECEMBER 7, 2023

Welcome to the comprehensive guide for beginners on harnessing the power of Microsoft's remarkable data visualization tool - Power BI. In today's data-driven world, the ability to transform raw data into meaningful insights is paramount, and Power BI empowers users to achieve just that.

BI 52

BI Raw Data Datasets Business Intelligence 52

Ascend.io

JANUARY 3, 2023

But most importantly, it should focus on the building of value with that data. In this article, let’s explore how “Data as a Product” thinking can deliver better value from data to end users in more useful and approachable ways.

Data 52

Data Data Lake Business Intelligence Big Data 52

Monte Carlo

JUNE 29, 2021

Data scientists, analysts, database engineers, data architects, and back-end engineers have been handling the ingestion, transformation, testing, and infrastructure work required to build and scale data platforms for years; if you haven’t read Maxime Beauchemin’s landmark article about this phenomenon, I highly recommend it.

Data Engineering 40

Data Engineering Data Engineer Engineering Recruitment 40

Confluent

FEBRUARY 21, 2019

During a recent talk titled Hunters ATT&CKing with the Right Data , which I presented with my brother Jose Luis Rodriguez at ATT&CKcon, we talked about the importance of documenting and modeling security event logs before developing any data analytics while preparing for a threat hunting engagement.

Process 81

Process Kafka Datasets SQL 81

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Cloudera partners are also benefiting from Apache Iceberg in CDP.

Cloud 79

Cloud Metadata Google Cloud Data Warehouse 79

Data Engineering Weekly

NOVEMBER 20, 2022

link] The short YouTube video gives a nice overview of the Data Cards. I found this article a bit late, but an exciting read for this week. We often think of AI/ ML as a complex data processing problem, but it doesn’t make any use until it is exposed to an end user or an application.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? Databricks – Databricks, the Apache Spark-as-a-service platform, has pioneered the data lakehouse, giving users the options to leverage both structured and unstructured data and offers the low-cost storage features of a data lake.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Monte Carlo

FEBRUARY 15, 2023

Data analysts and engineers can run the queries they want to run when they want to run them without worrying about excessive load times or statement timeouts. Yes, data warehouses can store unstructured data as a blob datatype. Data Transformation Raw data ingested into a data warehouse may not be suitable for analysis.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

Ascend.io

JULY 28, 2023

This article aims to shed light on the essential components of successful data pipeline architectures and offer actionable advice for creating scalable, reliable, and resilient data pipelines. This framework encompasses the steps of data ingestion, transformation, orchestration, and sharing.

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

Zalando Engineering

MARCH 21, 2017

Our most recent product requires precise estimates of future interests of Zalando consumers based on their history of interacting with the fashion platform. For example, we want to predict a consumer's interest in ordering selected fashion articles. This necessitates frequent re-training and model deployment.

Deep Learning 52

Deep Learning Raw Data Machine Learning AWS 52

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 84

Engineering Raw Data Data Science Scala 84

Rockset

SEPTEMBER 3, 2020

After discussing what PostgreSQL is, this article will look at how to offload read operations to it. But, if your application deals with a lot of unstructured data coming from a variety of sources, this option might not be a good fit. We’ll also examine some of the tradeoffs that accompany this choice. What Is PostgreSQL?

MongoDB 40

MongoDB PostgreSQL SQL Database 40

Confluent

MAY 7, 2019

There is no way that one computer node will ever be able to ingest and process all the events that get generated in real time. We therefore need a way of splitting up the data ingestion work. Data consumption continues to sail smoothly. In the span of this article, we defined what a consumer is and how it works.

Kafka 111

Kafka Accessible Accessibility Metadata 111

ProjectPro

OCTOBER 20, 2021

It has automated components of the traditional ML Flow from data acquisition, experimentation and even logging—definitely, a must-try within the Azure ecosystem. Vertex AI (Google) : Google recently (May 2021) launched a unified AI platform to build, deploy and scale machine learning models for individuals and enterprises.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

Netflix Tech

DECEMBER 14, 2018

MDVS also serves as the storehouse and the manager for the data schema itself. As was noted in the previous post , data schema could itself evolve over time, but all the data, ingested hitherto, has to remain compliant with the latest schema. This is described more in-depth later in this article.

Media 94

Media Database Metadata Data Schemas 94

Confluent

OCTOBER 10, 2019

In the IoT environment, for example, a large number of protocols for data exchange have developed in recent years. Although MQTT is the focus of this blog post, in a future article I will cover MQTT integration with IIoT and its proprietary protocols, like Siemens S7, Modbus, and ADS, through leveraging PLC4X and its Kafka integration.

Kafka 20

Kafka Google Cloud Architecture Machine Learning 20

Monte Carlo

MARCH 28, 2023

If you don’t like change, data engineering is not for you. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT.

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

Towards Data Science

APRIL 3, 2023

The post-modern data stack is coming. If you don’t like change, data engineering is not for you. The most prominent, recent examples are Snowflake and Databricks disrupting the concept of the database and ushering in the modern data stack era. Shane Murray co-authored this article. Are we ready?

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Monte Carlo

JULY 18, 2023

A decade later, a considerable amount of innovation in the data management industry is revolving around how different data platforms are coupling or decoupling storage and compute (don’t worry I include examples in the next section). Why are these things related, and more importantly, why should data leaders care?

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Rockset

FEBRUARY 14, 2022

That requires democratizing access to data, taking it from the C-suite and the data scientists training their ML models to every operational employee or customer who would stand to benefit. You can’t build a data-driven culture relying on batch-based analytics and BI. Not your customers, nor even your internal employees.

BI 52

BI Data Warehouse ETL Tools Data Lake 52

Monte Carlo

JULY 18, 2023

A decade later, a considerable amount of innovation in the data management industry is revolving around how different data platforms are coupling or decoupling storage and compute (don’t worry I include examples in the next section). Why are these things related, and more importantly, why should data leaders care?

Metadata 40

Metadata Data Warehouse Data Lake Government 40

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

Building 52

Building BI Data Lake Data Governance 52

Knowledge Hut

DECEMBER 13, 2023

Big Data startups compete for market share with the blue-chip giants that dominate the business intelligence software market. This article will discuss the top big data consulting companies , big data marketing companies , big data management companies and the biggest data analytics companies in the world.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

AltexSoft

JULY 8, 2021

While the origins of propensity modeling can be traced back to 1983, it’s only recently that machine learning has made it possible to unfold the technique’s full potential. With the right tools and experienced data science teams, companies can now build advanced propensity models and make accurate predictions. Collecting relevant data.

Machine Learning 78

Machine Learning Algorithm Education Data Science 78

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