Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Ascend.io

FEBRUARY 23, 2024

You are a data professional. Exciting, isn’t it Yet, embarking on the AI adoption journey introduces a series of challenges, with one of the most significant being the readiness of your data platform. In this article, we outline the essential prerequisites for an AI data platform.

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

Knowledge Hut

NOVEMBER 2, 2023

For those aspiring to build a career within the Azure ecosystem, navigating the choices between Azure Data Engineers and Azure DevOps Engineers can be quite challenging. Azure Data Engineers and Azure DevOps Engineers are two critical components of the Azure ecosystem for different but interconnected reasons.

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Manufacturing 109

Manufacturing Data Warehouse Kafka Retail 109

Towards Data Science

MAY 3, 2023

Data Engineering Learn about slow change dimensions (SCD) and how to implement SCD Type 2 in VDK Photo by Joshua Sortino on Unsplash Data is the backbone of any organization, and in today’s fast-paced world, it is crucial to keep track of its versions. They store and manage current and historical data in a data warehouse.

Data Lake 80

Data Lake Data SQL Data Warehouse 80

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

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. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Ascend.io

JANUARY 10, 2024

Visual representation of Conway’s Law ( source ) Read More: The Chief AI Officer: Avoid The Trap of Conway’s Law Process: Ensuring Data Readiness The backbone of successful AI implementation is robust data management processes. AI models are only as good as the data they consume, making continuous data readiness crucial.

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52

WeCloudData

OCTOBER 19, 2021

Executive Summary WeCloudData is one of the fastest growing Data & AI training companies in the world. Since 2016, WeCloudData has trained and helped thousands of students and clients level up their data skills and mature their data organizations.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Executive Summary WeCloudData is one of the fastest growing Data & AI training companies in the world. Since 2016, WeCloudData has trained and helped thousands of students and clients level up their data skills and mature their data organizations.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

SQL 52

SQL Kafka MongoDB MySQL 52

Ascend.io

JANUARY 3, 2023

Businesses are increasingly reliant on new technologies to enable the use of data in new and innovative ways. However, most data leaders are finding that technology alone does not cause the organization to deliver new and valuable insights fast enough. But most importantly, it should focus on the building of value with that data.

Data 52

Data Data Lake Business Intelligence Big Data 52

ProjectPro

JANUARY 19, 2022

Data Engineering is gradually becoming a popular career option for young enthusiasts. Explore this page further and learn everything about data engineers to find the answer. We will cover it all, from its definition, skills, responsibilities to the significance of data engineer in an institution. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Monte Carlo

APRIL 24, 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. But it’s not just our data platform that impacts how we define the problem and its solution.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

ProjectPro

FEBRUARY 25, 2022

What is a Machine Learning Pipeline? A machine learning pipeline helps automate machine learning workflows by processing and integrating data sets into a model, which can then be evaluated and delivered. A well-built pipeline helps in the flexibility of the model implementation.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion? Decision making would be slower and less accurate.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Ascend.io

JULY 28, 2023

Data pipelines are integral to business operations, regardless of whether they are meticulously built in-house or assembled using various tools. As companies become more data-driven, the scope and complexity of data pipelines inevitably expand. Ready to fortify your data management practice?

Data Pipeline 52

Data Pipeline Architecture Lambda Architecture Data Architecture 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Ascend.io

AUGUST 29, 2023

A star-studded baseball team is analogous to an optimized “end-to-end data pipeline” — both require strategy, precision, and skill to achieve success. Just as every play and position in baseball is key to a win, each component of a data pipeline is integral to effective data management.

Data Pipeline 52

Data Pipeline Pipeline-centric Database-centric Data Ingestion 52

Snowflake

JUNE 6, 2024

You can now use Snowflake Notebooks to simplify the process of connecting to your data and to amplify your data engineering, analytics and machine learning workflows. Leverage your existing role-based access controls (RBAC) to manage access to notebooks and the underlying data assets to enable consistent and robust data governance.

SQL 92

SQL Python Data Workflow Machine Learning 92

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Place?

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Ascend.io

FEBRUARY 6, 2023

If you’ve read this week’s release notes , you’ll have seen “Added ability to configure or override connection details at the Data Service level in BigQuery and Databricks Data Planes.” Data Services Listing with BigQuery, Snowflake, and Databricks. Data Service – is a group of Data Flows.

Cloud 52

Cloud Data Ingestion Raw Data Data Pipeline 52

Ascend.io

FEBRUARY 6, 2023

If you’ve read this week’s release notes , you’ll have seen “Added ability to configure or override connection details at the Data Service level in BigQuery and Databricks Data Planes.” Data Services Listing with BigQuery, Snowflake, and Databricks. Data Service – is a group of Data Flows.

Cloud 52

Cloud Data Ingestion Raw Data Data Pipeline 52

Monte Carlo

NOVEMBER 14, 2023

How data observability can increase data trust in Iceberg tables What is Apache Iceberg? Apache Iceberg is an open source data lakehouse table format developed by the data engineering team at Netflix to provide a faster and easier way to process large datasets at scale. Is your data lake a good fit for Iceberg?

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Snowflake

SEPTEMBER 11, 2023

How experimenting with Dynamic Tables on Snowflake led to improvements in the Data Vault patterns. So what exactly are Dynamic Tables and where should they fit into your Data Vault architecture? You can define a Dynamic Table to include SQL joins between data structures as views, tables or other Dynamic Tables.

SQL 70

SQL Data Raw Data Architecture 70

AltexSoft

JUNE 26, 2023

All successful companies do it: constantly collect data. While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Snowflake

MARCH 13, 2023

Discover how Gem built a context-aware threat response platform on Snowflake’s Data Cloud to offer its clients real-time detection and response in a single dashboard. Architecture designed to empower more clients Gem’s cybersecurity platform starts with raw data ingestion from its clients’ cloud environments.

Cloud 52

Cloud Building Data Ingestion AWS 52

ProjectPro

AUGUST 24, 2021

Most of us have observed that data scientist is usually labeled the hottest job of the 21st century, but is it the only most desirable job? For beginners or peeps who are utterly new to the data industry, Data Scientist is likely to be the first job title they come across, and the perks of being one usually make them go crazy.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. Cloud data warehouses solve these problems. Belonging to the category of OLAP (online analytical processing) databases, popular data warehouses like Snowflake, Redshift and Big Query can query one billion rows in less than a minute.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

U-Next

JUNE 29, 2022

What Are The Main Components Of Big Data? The ecosystems of big data are akin to ogres. Layers of big data components compiled together to form a stack, and it isn’t as straightforward as collecting data and converting it into knowledge. . The main components of big data types: . Transformation.

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

Knowledge Hut

JANUARY 18, 2024

I’ve often noticed that people use terms like Data Science and Artificial Intelligence ( AI ) interchangeably. The key connection between Data Science and AI is data. Some may argue that AI and Machine Learning fall within the broader category of Data Science , but it's essential to recognize the subtle differences.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! “Data analytics is the future, and the future is NOW!

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. 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.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Zalando Engineering

MARCH 21, 2017

Most prominently, they operate directly on sequences of data and thus are a perfect fit for modeling consumer histories. Instead, we can focus on building a flexible and versatile model that can be easily extended to new types of input data and applied to a variety of prediction tasks. That is, we do not use customer data.)

Deep Learning 52

Deep Learning Raw Data Machine Learning AWS 52

AltexSoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. And that’s the most important thing: Big Data analytics helps companies deal with business problems that couldn’t be solved with the help of traditional approaches and tools.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Confluent

OCTOBER 16, 2019

Trains are an excellent source of streaming data—their movements around the network are an unbounded series of events. Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. As with any real system, the data has “character.”

Kafka 19

Kafka Building Data Coding 19

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