Cloudera

DECEMBER 1, 2023

It focuses on five key pillars: investing in research and development; unleashing government AI resources; setting standards and policy; building the AI workforce; and advancing trust and security. Governance is another crucial aspect that cannot be overlooked. million), among others.

Building 104

Building Government Transportation Data Governance 104

Data Engineering Podcast

MARCH 9, 2020

Summary Data governance is a complex endeavor, but scaling it to meet the needs of a complex or globally distributed organization requires a well considered and coherent strategy. We have partnered with organizations such as O’Reilly Media, Corinium Global Intelligence, ODSC, and Data Council.

Data Governance 100

Data Governance Government Architecture Data 100

Databand.ai

AUGUST 30, 2023

Building a Winning Data Quality Strategy: Step by Step Eitan Chazbani August 30, 2023 What Is a Data Quality Strategy? A data quality strategy details the processes, tools, and techniques employed to ensure your company’s data is accurate, consistent, complete, and up-to-date.

Building 52

Building Data Cleanse Data Governance Datasets 52

Data Engineering Podcast

DECEMBER 7, 2020

Summary Building data products are complicated by the fact that there are so many different stakeholders with competing goals and priorities. Different organizations have tried a multitude of organizational strategies to improve the success rate of these data teams with varying levels of success.

Building 100

Building Big Data Consulting Data Engineering 100

Snowflake

MARCH 27, 2024

As organizations seek to drive more value from their data, observability plays a vital role in ensuring the performance, security and reliability of applications and pipelines while helping to reduce costs. One of our partners in this area is Observe , which offers a SaaS observability product that is built and operated on the Data Cloud.

Cloud 117

Cloud Data Governance Government Data 117

The Modern Data Company

APRIL 15, 2024

With this in mind, let’s explore how to demystify the process of building your data-driven strategy, making it accessible and actionable. We’ll uncover how you can transform data into a strategic asset that propels your organization forward without getting lost in the complexity of its creation.

Building 52

Building Raw Data Food Data 52

Data Engineering Podcast

NOVEMBER 9, 2020

Summary A data catalog is a critical piece of infrastructure for any organization who wants to build analytics products, whether internal or external. While there are a number of platforms available for building that catalog, many of them are either difficult to deploy and integrate, or expensive to use at scale.

Building 100

Building PostgreSQL BI Metadata 100

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

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

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

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

DECEMBER 14, 2020

In this episode Andrew Gross, Bobby Muldoon, and Anup Segu describe the self service data platform that they have built to allow data analysts to own the end-to-end delivery of data projects and how that has allowed them to scale their output. If you hand a book to a new data engineer, what wisdom would you add to it?

Data Analytics 100

Data Analytics Building MySQL Data 100

DareData

JULY 5, 2023

Learn how we build data lake infrastructures and help organizations all around the world achieving their data goals. In today's data-driven world, organizations are faced with the challenge of managing and processing large volumes of data efficiently.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services.

Architecture 130

Architecture Technology Google Cloud Metadata 130

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

Data Engineering Weekly

MARCH 3, 2024

There will be food, networking, and real-world talks around data engineering. Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 4) Building Data Products and why should you?

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

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

Snowflake

SEPTEMBER 11, 2023

Many customers evaluating how to protect personal information and minimize access to data look specifically to data governance in Snowflake features. There are a number of data governance operating models that I see working with Snowflake as a centralized data repository for personal information.

Cloud 75

Cloud Electronics Government Data Governance 75

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

Precisely

MAY 13, 2024

If you’re in the market for a data integration solution, there are many things to consider – including the flexibility of integration solutions, the availability of a strong network of service providers, and the vendor’s reputation for thought leadership in the integration space. A notable capability that achieves this is the data catalog.

Data Integration 52

Data Integration Metadata Amazon Web Services Data Governance 52

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. Strategies for Improving Data Quality 1.

Data Cleanse 85

Data Cleanse Datasets Data Governance Data Validation 85

Precisely

JANUARY 9, 2023

The pandemic also drove greater demand for self-service models, which allowed more users across the business to leverage data-driven insights, but also made it much harder to spot data quality issues as they occur. As data initiatives become more sophisticated, organizations will uncover new data quality challenges.

Data Integration 81

Data Integration Data Governance Government Data 81

Towards Data Science

JUNE 8, 2023

This post will focus on the most common team ownership models including: data engineering, data reliability engineering, analytics engineering, data quality analysts, and data governance teams. Why is data quality ownership important? The governance team treats every team output as a data product.

Data Governance 79

Data Governance Government Generalist Data Engineering 79

Snowflake

FEBRUARY 21, 2024

Customers are simplifying their architectures by using Hybrid Tables for a variety of use cases, including storing app and workflow state, serving data and building lightweight transactional applications. Get started quickly with the syntax you know Hybrid Tables are easy to use and simple to manage. What’s next?

Government 98

Government AWS Data Architect Architecture 98

The Modern Data Company

JULY 31, 2023

Consensus in Data Products: The first direct bridge between Data Initiatives & Business Like all good things, administering Data Products too is a combination of technology, culture, and process. People Angle : To treat data as a product, high-quality product managers must be assigned to the case.

Government 98

Government Data Governance Architecture Data Pipeline 98

Monte Carlo

JUNE 6, 2023

This post will focus on the most common team ownership models including: data engineering, data reliability engineering, analytics engineering, data quality analysts, and data governance teams. Table of Contents Why is important to answer who is responsible for data quality?

Data Governance 98

Data Governance Government Data Data Engineering 98

Data Engineering Podcast

MAY 18, 2024

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. The team at Zenlytic have leaned on the promise of large language models to build an AI agent that lets you converse with your data. Data lakes are notoriously complex.

Building 278

Building Data Lake High Quality Data Business Intelligence 278

LinkedIn Engineering

JUNE 2, 2023

This requires us to carefully manage the data which we collect and use and to leverage secure data infrastructures for storing and processing the data. Availability: Data must be readily available to the broader team in order to support their research and analysis.

Building 75

Building Banking Datasets Media 75

Precisely

MAY 8, 2023

In any strategic undertaking, trusted data is key to making better decisions that unlock new opportunities for your organization. One of the first steps in the process is to access and replicate the data you need to the cloud for robust analytics and reporting. Learn more Now, let’s talk about monitoring your data.

Government 52

Government Data Governance Data Integration Machine Learning 52

Snowflake

MARCH 5, 2024

To empower organizations to deliver fast wins with generative AI while keeping data secure when using LLMs, we are excited to announce Snowflake Cortex LLM functions are now available in public preview for select AWS and Azure regions. Figure 1: Multi-task accuracy of industry-leading LLMs based on MLLU benchmark. What is RAG?

Government 92

Government AWS Data Preparation Data Governance 92

Snowflake

MARCH 21, 2023

In February, Snowflake launched new features around streaming data ingestion and data governance and improved SQL experience and performance, with enhancements to Search Optimization Service and more. Climatiq Climatiq is providing the building blocks to achieve carbon intelligence, at scale.

Retail 70

Retail Healthcare Data Ingestion Consulting 70

Knowledge Hut

MARCH 20, 2024

Speaking from experience, the data engineers in this role are right in the thick of it all. From start to finish, Azure data engineer roles and responsibilities revolve around designing, implementing, and managing data solutions specifically tailored for the Azure platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Knowledge Hut

MARCH 15, 2024

Speaking from experience, the data engineers in this role are right in the thick of it all. From start to finish, Azure data engineer roles and responsibilities revolve around designing, implementing, and managing data solutions specifically tailored for the Azure platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

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

Precisely

DECEMBER 20, 2022

Read more > #4 4 Real-World Examples of Financial Institutions Making Use of Big Data Big data has moved beyond “new tech” status and into mainstream use. Within the financial industry, there are some specialized uses for data integration and big data analytics. Data governance provides the answer.

Data Governance 52

Data Governance Government Hadoop Big Data 52

Snowflake

JUNE 12, 2023

Founded in 2017, IMMO is on a mission to fix a broken real estate market, making it more equitable, safe, accountable, and accessible. We manage the entire lifecycle,” said Julian Derber, Senior Director and Head of Data at IMMO. “We Today, the company uses the Snowflake Data Cloud to achieve each of these things.

Technology 52

Technology Portfolio Data Governance Government 52

Cloudera

JUNE 22, 2023

The top-line benefits of a hybrid data platform include: Cost efficiency. A hybrid data platform enables the preservation of existing investments in legacy applications and workloads without modifying them. It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud.

Data Cleanse 65

Data Cleanse Data Governance Unstructured Data Cloud Storage 65