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 80

Data Governance Government Generalist Data Engineering 80

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

Cloudera

JUNE 22, 2023

It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud. Its built-in intelligence automates common data management and data integration tasks, improves the overall effectiveness of data governance, and permits a holistic view of data across the cloud and on-premises environments.

Data Cleanse 68

Data Cleanse Data Governance Unstructured Data Cloud Storage 68

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.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Cloudera

DECEMBER 11, 2020

The Data Security and Governance category, at the annual Data Impact Awards, has never been so important. At the same time, the need to have a strong layer of security and governance is being highlighted. This is what really stood out about the finalists of the Data Security and Governance category.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

AltexSoft

FEBRUARY 11, 2023

In the article, we explore the role of a data architect, discuss the responsibilities and required skills, and share what kind of companies may need such a specialist. What is a data architect? To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Edureka

FEBRUARY 7, 2023

An Azure Data Engineer is responsible for designing, implementing, and maintaining data management and data processing systems on the Microsoft Azure cloud platform. They work with large and complex data sets and are responsible for ensuring that data is stored, processed, and secured efficiently and effectively.

Data Engineering 52

Data Engineering Data Engineer Engineering Programming Language 52

Knowledge Hut

APRIL 23, 2024

Privacy and Security Concerns The chances of data in large volumes being vulnerable to security threats, data breaches, and cyberattacks are quite high. Unless it is safeguarded via modern tech means, data security is a very real threat.

Big Data 52

Big Data Media Government Big Data Skills 52

Databand.ai

JULY 19, 2023

Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database. This can be achieved manually, or automatically using a combination of software and hardware tools designed specifically for this task. It can also help to improve the accuracy and reliability of the data.

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Knowledge Hut

MARCH 26, 2024

Growing Technology Landscape: With the rapid advancements in technology, there's an increasing demand for professionals who can design and implement complex IT solutions. Role Level: Typically a senior-level position requiring extensive experience in architecture design and implementation across various domains and industries.

Amazon Web Services 52

Amazon Web Services Google Cloud Computer Science AWS 52

ProjectPro

FEBRUARY 8, 2023

ETL developers play a vital role in designing, implementing, and maintaining the processes that help organizations extract valuable business insights from data. ETL developer is a software developer who uses various tools and technologies to design and implement data integration processes across an organization.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Knowledge Hut

JANUARY 30, 2024

This data can be structured, semi-structured, or entirely unstructured, making it a versatile tool for collecting information from various origins. The extracted data is then duplicated or transferred to a designated destination, often a data warehouse optimized for Online Analytical Processing (OLAP).

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

AUGUST 29, 2023

The goal is to provide a comprehensive guide that can be a navigational tool for all specialists plotting their course in today’s data-driven world. What is a data lake? A data lake is a centralized repository designed to hold vast volumes of data in its native, raw format — be it structured, semi-structured, or unstructured.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. What is data governance? billion in 2020 to $5.28

Data Governance 52

Data Governance Government Healthcare Programming 52

Monte Carlo

FEBRUARY 6, 2023

In this post, we’ll examine some best practices for migrating your data to a cloud solution, show you how to develop your own migration strategy, and take a closer look at some popular cloud warehouse solutions that you might consider for your platform. Who has access to your new data warehouse? Let’s jump in!

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc. The rest of the exam details are the same as the DP-900 exam.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

François Nguyen

MARCH 7, 2021

In this article, Juan Sequada gives maybe one of the best definition of Data Mesh ” It is paradigm shift towards a distributed architecture that attempts to find an ideal balance between centralization and decentralization of metadata and data management.”

Government 130

Government Data Governance Data Metadata 130

Databand.ai

AUGUST 30, 2023

Integrating these principles with data operation-specific requirements creates a more agile atmosphere that supports faster development cycles while maintaining high quality standards. Organizations need to establish data governance policies, processes, and procedures, as well as assign roles and responsibilities for data governance.

Data Governance 40

Data Governance Data Cleanse Government Data Pipeline 40

Striim

FEBRUARY 19, 2024

Central to unlocking the potential of these frameworks is Striim, a platform that facilitates real-time data integration, analytics, and event processing, providing businesses can fully leverage their data. Approach: Data Mesh decentralizes data management, giving individual domains or teams control and responsibility for their data.

Data Integration 52

Data Integration Government Data Data Governance 52

Databand.ai

JULY 19, 2023

By loading the data before transforming it, ELT takes full advantage of the computational power of these systems. This approach allows for faster data processing and more flexible data management compared to traditional methods. The data pipeline should be designed to handle the volume, variety, and velocity of the data.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Knowledge Hut

SEPTEMBER 6, 2023

What Are Database Certifications Database certifications are invaluable credentials for professionals working within database environments as they validate one's proficiency in specific databases, which are akin to specialized tools designed for storing and retrieving critical information. Design and implement a SAP migration strategy.

Database 52

Database Certification MongoDB MySQL 52

Cloudera

OCTOBER 19, 2023

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

Telecommunication 78

Telecommunication Data Architecture Government Architecture 78

Precisely

MAY 1, 2023

Virtually every enterprise on the planet invests heavily in data. Integration, data quality, data governance, location intelligence, and enrichment are driving trust and delivering value. How can organizations maximize their ROI on their investments in data integrity?

Food 52

Food Consulting Pharmaceutical Manufacturing 52

Knowledge Hut

SEPTEMBER 26, 2023

Data visualization skills to create visuals, such as charts or graphs that can be used for decision making. How to create interactive dashboards Designing an effective dashboard layout which opens a combination of visuals, text boxes, and images. Setting up the drill down features that allow users to explore data in detail.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . helps data engineers and data architects to design, build and maintain robust and reliable data systems.

Consulting 123

Consulting Machine Learning Data Science Data Pipeline 123

AltexSoft

NOVEMBER 10, 2021

Well, there’s a new phenomenon in data management that received the name of a data lakehouse. 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. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Picnic Engineering

JULY 26, 2022

Data Mesh, or Hub-and-Spoke? and other reflections on building data governance. What exactly is a “lakeless” Data Warehouse? The adjective “lakeless” simply emphasizes that we are strong believers in governed analytical data management. The most important thing for a successful analytics strategy.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

AltexSoft

NOVEMBER 23, 2021

Implementing data virtualization requires fewer resources and investments compared to building a separate consolidated store. Enhanced data security and governance. The information doesn’t need to be moved anywhere and access levels can be managed. How to get started with data virtualization. onsuming layer.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

JANUARY 31, 2022

Traditional data preparation platforms, including Apache Spark, are unnecessarily complex and inefficient, resulting in fragile and costly data pipelines. Snowflake's machine learning partners transfer most of their automated feature engineering down into Snowflake's cloud data platform.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

It offers a fault-tolerant storage engine that prioritizes data security. Delta Lake Source: Github Delta Lake is an open-source project that allows you to create a Lakehouse design based on data lakes. It's an open-source database and data management framework.

Big Data 52

Big Data Project Metadata Programming Language 52

Cloudera

OCTOBER 7, 2021

Introduction to the Data Mesh Architecture. The concept of the data mesh architecture is not entirely new; Its conceptual origins are rooted in the microservices architecture, its design principles (i.e., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Architecture 127

Architecture Metadata Government Kafka 127

AltexSoft

MAY 12, 2023

Unstructured data refers to information that lacks a predefined format or organization. In contrast, big data refers to large volumes of structured and unstructured data that are challenging to process, store, and analyze using traditional data management tools. Data security and privacy.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Monte Carlo

MAY 31, 2023

Here are some of the requirements you’ll need to define at the outset of developing your data integrity framework: Regulatory requirements According to Compliance Online , regulatory requirements for data integrity include: Frequent, comprehensive data back-ups Physical data security (i.e.,

Building 52

Building Data Validation Healthcare Data Integration 52

Cloudera

AUGUST 26, 2020

Informatica’s comprehensive suite of Data Engineering solutions is designed to run natively on Cloudera Data Platform — taking full advantage of the scalable computing platform. Data scientists can also automate machine learning with the industry-leading H2O.ai’s AutoML Driverless AI on data managed by Cloudera.

Machine Learning 83

Machine Learning BI Big Data Data Warehouse 83

ProjectPro

MAY 1, 2018

Zoomlion, the chinese construction machinery and sanitation equipment manufacturer adopted Cloudera’s big data platform to serve its growing big data needs. Zoomlion will use Cloudera’s big data platform to provide data management and analytic services to its customers in over 100 countries across 6 continents.

Hadoop 40

Hadoop Banking Healthcare Food 40

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64

phData: Data Engineering

JULY 18, 2023

To truly understand its potential, we need to explore the benefits it brings, particularly when transitioning from traditional data management structures. Why Migrate to a Modern Data Stack? Zero Copy Cloning: Create multiple ‘copies’ of tables, schemas, or databases without actually copying the data.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52