The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. What factors are most important when building a data management ecosystem?

Data Management 52

Data Management Data Lake Management Data Warehouse 52

Snowflake

OCTOBER 5, 2023

Learn how Europe’s leading embedded finance provider delivers data faster, decentralizes access and improves lineage controls with Snowflake’s Data Cloud. But while our existing provider offers amazing solutions, we found a few challenges in how we had to manage data access and lineage.”

Accessible 64

Accessible Accessibility Finance Banking 64

Data Engineering Podcast

FEBRUARY 20, 2022

Summary The life sciences as an industry has seen incredible growth in scale and sophistication, along with the advances in data technology that make it possible to analyze massive amounts of genomic information. Interview Introduction (see Guy’s bio below) How did you get involved in the area of data management?

Systems 100

Systems Software Engineer Software Engineering Data Warehouse 100

ProjectPro

FEBRUARY 16, 2023

With so much riding on the efficiency of ETL processes for data engineering teams, it is essential to take a deep dive into the complex world of ETL on AWS to take your data management to the next level. AWS refers to Amazon Web Service, the most widely used cloud computing system.

AWS 52

AWS Data Management ETL Tools Management 52

Data Engineering Podcast

SEPTEMBER 3, 2018

Summary With the proliferation of data sources to give a more comprehensive view of the information critical to your business it is even more important to have a canonical view of the entities that you care about. Can you start by establishing a definition of data mastering that we can work from?

Data Management 100

Data Management Management Relational Database Business Intelligence 100

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. End-to-end Data Lifecycle.

Technology 87

Technology Data Management Management Insurance 87

Knowledge Hut

APRIL 23, 2024

We live in a data-driven culture where familiarity with databases is crucial. Database management is crucial for businesses of all sizes to guarantee that their data is complete, safe, and easily available when needed. Why are Database Management Skills Important? In this section, we'll examine every skill in depth.

Database 52

Database Management Relational Database SQL 52

Data Engineering Podcast

JULY 27, 2020

Summary A majority of the scalable data processing platforms that we rely on are built as distributed systems. Kyle Kingsbury created the Jepsen framework for testing the guarantees of distributed data processing systems and identifying when and why they break. Can you start by describing what the Jepsen project is?

Systems 100

Systems Building Scala Java 100

Data Engineering Podcast

JULY 20, 2020

Summary Wind energy is an important component of an ecologically friendly power system, but there are a number of variables that can affect the overall efficiency of the turbines. Michael Tegtmeier founded Turbit Systems to help operators of wind farms identify and correct problems that contribute to suboptimal power outputs.

Systems 100

Systems Machine Learning Manufacturing Algorithm 100

Cloudera

JANUARY 26, 2024

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. In a good data governance strategy, it is important to define roles that allow the business to limit the level of access that users can have to their strategic data assets.

Metadata 73

Metadata Data Governance Government Management 73

Data Engineering Podcast

MAY 6, 2019

Summary The database market continues to expand, offering systems that are suited to virtually every use case. In this episode Ryan Worl explains how it is architected, how to use it for your applications, and provides examples of system design patterns that can be built on top of it. How are conflicts managed?

Systems 100

Systems MongoDB NoSQL Database 100

Cloudera

MARCH 4, 2024

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. In a good data governance strategy, it is important to define roles that allow the business to limit the level of access that users can have to their strategic data assets.

Metadata 52

Metadata Data Governance Government Management 52

Data Engineering Podcast

AUGUST 24, 2020

Summary In order to scale the use of data across an organization there are a number of challenges related to discovery, governance, and integration that need to be solved. The key to those solutions is a robust and flexible metadata management system. If you hand a book to a new data engineer, what wisdom would you add to it?

Metadata 100

Metadata Management Kafka Data Engineering 100

Snowflake

APRIL 8, 2024

BigGeo BigGeo accelerates geospatial data processing by optimizing performance and eliminating challenges typically associated with big data. Implentio Implentio is a centralized tool that helps ecommerce ops and finance teams efficiently and cost-effectively manage fulfillment and logistics spending.

Pipeline-centric 125

Pipeline-centric Food Healthcare Unstructured Data 125

Data Engineering Podcast

JULY 27, 2021

Datastax has recently introduced a new managed offering for Pulsar workloads in the form of Astra Streaming that lowers those barriers and make stremaing workloads accessible to a wider audience. What are some of the supporting systems that are necessary to power that workflow?

Building 100

Building Management Kafka Data Warehouse 100

Data Engineering Podcast

MAY 26, 2024

Summary Any software system that survives long enough will require some form of migration or evolution. When that system is responsible for the data layer the process becomes more challenging. Sriram Panyam has been involved in several projects that required migration of large volumes of data in high traffic environments.

Systems 130

Systems Data Lake High Quality Data Google Cloud 130

Knowledge Hut

DECEMBER 26, 2023

A growing amount of information is becoming digital and accessible through wireless and wired digital communication networks in addition to the pervasive internet. Cybersecurity is defending sensitive data and important systems from online threats. The security of sensitive information is another issue covered by data security.

Hospitality 98

Hospitality Finance Electronics Retail 98

Snowflake

APRIL 29, 2024

The second batch of DORA policy products, which aims to strengthen oversight and risk management for third-party ICT providers, is currently under development. Identification of potential threats through data analysis and risk assessment processes to shift toward more proactive risk management. Five Core Pillars of DORA 1.

Transportation 82

Transportation Data Governance Government Consulting 82

Data Engineering Podcast

MARCH 18, 2023

He also explains why data security is distinct from application security and some methods for reducing the challenge of working across different data systems. From March 28-30th 2023, they'll play host to hundreds of attendees, 100 top speakers, and dozens of startups that are advancing data science, engineering and AI.

Data Security 130

Data Security Machine Learning Data Science Metadata 130

Cloudera

FEBRUARY 7, 2024

How enterprise-grade data management creates better and more efficient care. Relocation wasn’t possible, so he installed cameras, shared access computer capabilities, phone screening services, and microphones in his father’s home in London.

Medical 98

Medical Healthcare Hospitality Insurance 98

Databand.ai

AUGUST 30, 2023

Data consistency refers to the state of data in which all copies or instances are the same across all systems and databases. Consistency ensures that data is accurate, up-to-date, and coherent across different database systems, applications, and platforms. Data consistency is essential for various reasons.

Data Integration 52

Data Integration Data Cleanse Data Validation High Quality Data 52

Knowledge Hut

JANUARY 18, 2024

The opportunities are endless in this field — you can get a job as an operation analyst, quantitative analyst, IT systems analyst, healthcare data analyst, data analyst consultant, and many more. A Python with Data Science course is a great career investment and will pay off great rewards in the future. Choose data sets.

Data Science 98

Data Science Business Analyst ETL Method Data Architect 98

Knowledge Hut

NOVEMBER 16, 2023

Designed for agility and versatility, the CCNA certifies your ability to manage and operate today's most complex networks. The Cisco Certified Network Practitioner (CCNP) certification training course teaches candidates the following: Scalable internet works Remote access Advanced routtng How to install and maintain WAN and LAN system 3.

Technology 98

Technology MySQL MongoDB Google Cloud 98

Knowledge Hut

MARCH 7, 2024

Syncing Across Data Sources Once you import data into Big Data platforms you may also realize that data copies migrated from a wide range of sources on different rates and schedules can rapidly get out of the synchronization with the originating system.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Databand.ai

MAY 30, 2023

Here are several reasons data quality is critical for organizations: Informed decision making: Low-quality data can result in incomplete or incorrect information, which negatively affects an organization’s decision-making process. A complete dataset allows for more comprehensive analysis and decision-making.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Knowledge Hut

APRIL 23, 2024

It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques. Small Data on the other hand, represents relatively smaller data sizes, typically in the order of gigabytes or less. Small Data: Managing privacy and security in Small Data is comparatively easier.

Big Data 52

Big Data Datasets Data Analysis Media 52

Knowledge Hut

APRIL 23, 2024

With the advent of technology and the arrival of modern communications systems, computer science professionals worldwide realized big data size and value. As big data evolves and unravels more technology secrets, it might help users achieve ambitious targets. Take patient management systems as an example.

Big Data 52

Big Data Media Government Big Data Skills 52

Knowledge Hut

APRIL 23, 2024

For example, in 1880, the US Census Bureau needed to handle the 1880 Census data. They realized that compiling this data and converting it into information would take over 10 years without an efficient system. Thus, it is no wonder that the origin of big data is a topic many big data professionals like to explore.

Big Data 52

Big Data Amazon Web Services Media Cloud Computing 52

Striim

MAY 1, 2024

UPS Capital recognizes the challenges faced by its customers in securing their package delivery ecosystem and is harnessing digital capabilities and data access to redefine traditional approaches, ensuring improved customer experiences and combating shipping loss.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

The Modern Data Company

FEBRUARY 15, 2023

Maintaining a clear strategy for gathering, storing, and labeling data is challenging. Limited resources: Data management has always been resource intensive, but not all organizations can maintain a full data team. Without suitable resources for company-wide data management, it’s easier to fall behind.

Government 98

Government Data Governance Raw Data Data 98

Knowledge Hut

APRIL 25, 2024

If you pursue the MSc big data technologies course, you will be able to specialize in topics such as Big Data Analytics, Business Analytics, Machine Learning, Hadoop and Spark technologies, Cloud Systems etc. Look for a suitable big data technologies company online to launch your career in the field.

Big Data 98

Big Data Technology NoSQL Hadoop 98

Edureka

MAY 6, 2024

MLOps is an emerging discipline that aims to unify and streamline the machine learning system development (Dev) and operations (Ops) lifecycle. MLOps refers to the practice and discipline within machine learning that aims to unify and streamline machine learning system development (Dev) and operations (Ops).

Machine Learning 52

Machine Learning Metadata Programming Language Healthcare 52

Snowflake

FEBRUARY 5, 2024

The foundation for success is a data platform that allows flexible, cost-effective ways to access gen AI — whether organizations want to use off-the-shelf commercial and open-source large language models (LLMs), or fine-tune their own LLMs for more complex applications. Rinesh Patel, Snowflake’s Global Head of Financial Services 2.

Unstructured Data 97

Unstructured Data Banking Government Insurance 97

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Effective Data Anomaly Monitoring (#2) Introduction Ensuring the accuracy and timeliness of data ingestion is a cornerstone for maintaining the integrity of data systems. This comprehensive approach allows data teams to: Quickly find and rectify problematic data.

Data Ingestion 52

Data Ingestion Transportation High Quality Data Data Schemas 52

Knowledge Hut

DECEMBER 29, 2023

Career Options: This specialty may prepare you for positions such as: Computer systems analyst Computer network analyst Data scientist Data analyst Data Engineer Data manager D. The implementation of distributed computing systems is often called "cloud computing."

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Databand.ai

AUGUST 30, 2023

The DataOps framework is a set of practices, processes, and technologies that enables organizations to improve the speed, accuracy, and reliability of their data management and analytics operations. The core philosophy of DataOps is to treat data as a valuable asset that must be managed and processed efficiently.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Towards Data Science

DECEMBER 15, 2023

Taking a hard look at data privacy puts our habits and choices in a different context, however. Data scientists’ instincts and desires often work in tension with the needs of data privacy and security. Anyone who’s fought to get access to a database or data warehouse in order to build a model can relate.

Machine Learning 93

Machine Learning Data Science Data Security Data Storage 93