Business Intelligence, Data Engineering, Government and Infrastructure

Fundamentals of Data Engineering

Xebia

JANUARY 19, 2023

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. The authors state that the target audience is technical people and, second, business people who work with technical people. Nevertheless, I strongly agree.

Data Engineering

Data Engineering Engineering Data Technical Review

5 tips for excelling at self-service analytics

CIO

NOVEMBER 9, 2022

But experienced data analysts and data scientists can be expensive and difficult to find and retain. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities. “It Have a data governance plan as well to validate and keep the metrics clean.

Analytics

Analytics Metrics Government Business Intelligence

Manta, a data observability startup, raises $35M to grow its workforce

TechCrunch

MAY 26, 2022

Insights gleaned from error-filled spreadsheets or business intelligence apps could lead to poor decisions that may be costly and damage the business,” Kratky told TechCrunch in an email interview. “Data lineage and observability are key capabilities that can solve these complex issues.

Data

Data Weak Development Team Enterprise Analysis

Data Architect: Role Description, Skills, Certifications and When to Hire

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? machine learning and deep learning models; and business intelligence tools. Feel free to enjoy it.

Data

Data Data Engineering Big Data Architecture

How companies are building sustainable AI and ML initiatives

O'Reilly Media - Ideas

JANUARY 29, 2019

In 2018, we decided to run a follow-up survey to determine whether companies’ machine learning (ML) and AI initiatives are sustainable—the results of which are in our recently published report, “ Evolving Data Infrastructure.”. Data scientists and data engineers are in demand.

Sustainability

Sustainability Company Machine Learning Artificial Inteligence

Core technologies and tools for AI, big data, and cloud computing

O'Reilly Media - Ideas

FEBRUARY 11, 2019

In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. At Strata Data San Francisco, Netflix , Intuit , and Lyft will describe internal systems designed to help users understand the evolution of available data resources.

Big Data

Big Data Technology Tools Cloud

Enabling privacy and choice for customers in data system design

Lacework

NOVEMBER 1, 2023

In many cases we see that customers prefer to have their data stored and managed locally in their home region, both for reasons of regulatory compliance and also business preference. The data replication may be performed leveraging the warehouse recovery tool, which is performed over a secure infrastructure using end to end encryption.

System Design

System Design Systems Review System Data

Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data

Data Analytics Cloud Technical Review

How a modern data platform supports government fraud detection

Cloudera

NOVEMBER 19, 2020

November 15-21 marks International Fraud Awareness Week – but for many in government, that’s every week. From bogus benefits claims to fraudulent network activity, fraud in all its forms represents a significant threat to government at all levels. The Public Sector data challenge. Modernization has been a boon to government.

Government

Government Artificial Inteligence Machine Learning Data

Cost Conscious Data Warehousing with Cloudera Data Platform

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. You have a centralized data catalog and schema registry.

Data

Data Technical Review Storage Systems Review

What is Microsoft Fabric and Why Should You Care?

Datavail

JUNE 15, 2023

“It unifies the business model across all the different types of analytics workloads, whether they’re SQL, machine learning – whatever job you want, you can use the same compute infrastructure. Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources.

Azure

Azure Analytics Storage Generative AI

Data Summit 2023 Event Recap

Datavail

JUNE 8, 2023

Data Summit 2023 was filled with thought-provoking sessions and presentations that explored the ever-evolving world of data. From the technical possibilities and challenges of new and emerging technologies to using Big Data for business intelligence, analytics, and other business strategies, this event had something for everyone.

Database Administration

Database Administration Data Artificial Inteligence Analytics

Data Mesh Architecture: Concept, Main Principles, and Implementation

Altexsoft

JULY 19, 2022

The HR team will manage all of this data and generate datasets to be consumed by other users in the company like the marketing team. They also own the governance of their domain. It’s easiest to understand the concept of a data mesh by looking at the core principles behind it which we’re going to uncover more extensively later on.

Architecture

Architecture Data Analytics Data Engineering

Next Stop – Building a Data Pipeline from Edge to Insight

Cloudera

FEBRUARY 8, 2021

Security & Governance – an integrated set of security, management and governance technologies across the entire data lifecycle. 1 The enterprise data lifecycle. Data Enrichment Challenge. Building a Pipeline Using Cloudera Data Engineering. 2 ECC data enrichment pipeline. Conclusion.

Data

Data Technical Review Data Engineering Analysis

Automating Data Pipelines in CDP with CDE Managed Airflow Service

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. With Airflow based pipelines in DE, customers can now specify their data pipeline using a simple python configuration file.

Data

Data Open Source Government Analytics

DataOps: Adjusting DevOps for Analytics Product Development

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics

Analytics DevOps Development Software Review

Trends in Cloud Jobs In 2019

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding. Business Intelligence Analyst.

Trends

Trends Cloud IoT Artificial Inteligence

Implementing a Data Management Strategy: Key Processes, Main Platforms, and Best Practices

Altexsoft

OCTOBER 2, 2020

Data architecture is a starting point for any data management model. Fitting into wider enterprise architecture, it outlines how data is collected, integrated, transformed, stored, and used. A data architect focuses on building a robust infrastructure so that data brings business value.

Database Administration

Database Administration Strategy Data Technical Review

Building a Self-Managed Shared Data Experience

Cloudera

DECEMBER 7, 2017

Cloud offers elasticity of those resources to efficiently support transient analytics workloads and data pipelines. Cloud offers self-service without waiting for IT infrastructure and operations teams. That data may be stored multiple times in different pools, each multiplying storage resource costs.

Data

Data Machine Learning Artificial Inteligence Analytics

Procurement Analytics: Challenges, Opportunities, and Implementation Approaches

Altexsoft

NOVEMBER 9, 2021

However, you have to remember that ML approaches are about building and maintaining complicated data infrastructures which requires significant investment and computing power. formatting, content, security, archiving, connections with government institutions, and so on. Procurement analytics infrastructure. Extract data.

Analytics

Analytics Software Review Systems Review Technical Review

The Good and the Bad of Hadoop Big Data Framework

Altexsoft

JULY 29, 2022

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. According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Hadoop ecosystem.

Big Data

Big Data Data Google Cloud Storage

The Good and the Bad of Snowflake Data Warehouse

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. BTW, we have an engaging video explaining how data engineering works. Hidden costs.

Weak Development Team

Weak Development Team Data Storage Technical Review

IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

Altexsoft

OCTOBER 8, 2021

Based on the requirements, there are plenty of transformation operations available to manipulate data including split, join, filter, and others. As ODI supports both ETL and ELT data infrastructures, transformations can happen either in the staging area before data is loaded into a destination or after loading.

Tools

Tools Data Software Review Open Source

How to Successfully Implement HR Analytics and People Analytics in a Company

Altexsoft

OCTOBER 3, 2019

Deloitte reports that The Ministry of Energy of the Government of Mexico uses a predictive workforce planning and analytics model to learn about the current shortage of skilled workers in the oil and gas industry and predict one over a 10-year horizon. Data engineer builds interfaces and infrastructure to enable access to data.

Analytics

Analytics Company Off-The-Shelf How To

How data science gives Games 24×7 a hyperpersonalized edge

CIO

MAY 11, 2023

With a portfolio spanning skill games (RummyCircle), fantasy sports (My11Circle), and casual games (U Games), the company banks firmly on technology to build a highly scalable gaming infrastructure that serves more than 100 million registered users across platforms. Depending on the use cases, we are using two platforms for data management.

Games

Games Artificial Inteligence Data Artificial Intelligence

Analytics Maturity Model: Levels, Technologies, and Applications

Altexsoft

DECEMBER 9, 2020

We will describe each level from the following perspectives: differences on the operational level; analytics tools companies use to manage and analyze data; business intelligence applications in real life; challenges to overcome and key changes that lead to transition. Data warehouse architecture.

Analytics

Analytics Technical Review Technology Applications

Data analytics: your complete guide to big data consulting

Agile Engine

DECEMBER 27, 2023

Introduction With the growing availability of cloud and AI, the data collected by organizations is now worth its weight in gold. Large-scale, granular, and actionable data analytics is more accessible than ever, but it still comes with numerous challenges. That’s where data analytics consultancies come into play.

Big Data

Big Data Analytics Data Analysis

The Good and the Bad of Databricks Lakehouse Platform

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.

Weak Development Team

Weak Development Team Machine Learning Artificial Inteligence Software Review

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

Altexsoft

MARCH 14, 2023

A modern data stack can help the company manage and analyze this data effectively by using cloud-based data warehouses like Snowflake , data integration tools like Stitch, and data visualization software like Power BI. Built around a cloud data warehouse, data lake, or data lakehouse.

Data

Data Technical Review Software Review Artificial Inteligence

CTO Universe

Fundamentals of Data Engineering

5 tips for excelling at self-service analytics

Trending Sources

Manta, a data observability startup, raises $35M to grow its workforce

Data Architect: Role Description, Skills, Certifications and When to Hire

How companies are building sustainable AI and ML initiatives

Core technologies and tools for AI, big data, and cloud computing

Enabling privacy and choice for customers in data system design

Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

How a modern data platform supports government fraud detection

Cost Conscious Data Warehousing with Cloudera Data Platform

What is Microsoft Fabric and Why Should You Care?

Data Summit 2023 Event Recap

Data Mesh Architecture: Concept, Main Principles, and Implementation

Next Stop – Building a Data Pipeline from Edge to Insight

Automating Data Pipelines in CDP with CDE Managed Airflow Service

DataOps: Adjusting DevOps for Analytics Product Development

Trends in Cloud Jobs In 2019

Implementing a Data Management Strategy: Key Processes, Main Platforms, and Best Practices

Building a Self-Managed Shared Data Experience

Procurement Analytics: Challenges, Opportunities, and Implementation Approaches

The Good and the Bad of Hadoop Big Data Framework

The Good and the Bad of Snowflake Data Warehouse

IBM InfoSphere vs Oracle Data Integrator vs Xplenty and Others: Data Integration Tools Compared

How to Successfully Implement HR Analytics and People Analytics in a Company

How data science gives Games 24×7 a hyperpersonalized edge

Analytics Maturity Model: Levels, Technologies, and Applications

Data analytics: your complete guide to big data consulting

The Good and the Bad of Databricks Lakehouse Platform

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

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