InfoWorld

FEBRUARY 9, 2024

It is built around a data lake called OneLake, and brings together new and existing components from Microsoft Power BI, Azure Synapse, and Azure Data Factory into a single integrated environment. In many ways, Fabric is Microsoft’s answer to Google Cloud Dataplex. As of this writing, Fabric is in preview.

Big Data 78

Big Data Data Azure Google Cloud 78

Altexsoft

MARCH 18, 2021

From the late 1980s, when data warehouses came into view, and up to the mid-2000s, ETL was the main method used in creating data warehouses to support business intelligence (BI). As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. Compliance.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Read why the future of data lakehouses is open.

Data 88

Data Analytics Artificial Inteligence Machine Learning 88

O'Reilly Media - Ideas

FEBRUARY 11, 2019

There are many articles that point to the explosion of data, but in order for that data that be useful for analytics and ML, it has to be collected, transported, cleaned, stored, and combined with other data sources. Data Platforms. Data Integration and Data Pipelines. Model lifecycle management.

Big Data 108

Big Data Technology Tools Cloud 108

Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

AUGUST 30, 2022

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Disparate systems create issues with transparency and compliance. Lack of sharing hinders the elimination of fraud, waste, and abuse.

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

John Snow Labs

FEBRUARY 12, 2025

It provides a suite of tools for data engineering, data science, business intelligence, and analytics. Answering questions about a clinical encounters principal diagnosis, test ordered, or a research abstracts study design or main outcomes Example: Question answering Model De-identification E.

Artificial Inteligence 52

Artificial Inteligence Azure Healthcare Software Review 52

Altexsoft

JANUARY 14, 2021

It is usually created and used primarily for data reporting and analysis purposes. Thanks to the capability of data warehouses to get all data in one place, they serve as a valuable business intelligence (BI) tool, helping companies gain business insights and map out future strategies. Integrations.

Backup 115

Backup Azure Software Review Architecture 115

Invid Group

AUGUST 28, 2024

External metrics can be implemented using Business Intelligence (BI) tools and shared with the clients to measure performance. They come in all flavors: different formats, templates, and from different legal processes, sizes, and quality. Internal metrics can be very technical, like hyperparameters, which can be tuned over time.

Technical Review 52

Technical Review Artificial Inteligence Performance Azure 52

InnovationM

MAY 14, 2023

Tools like Apache Atlas and Collibra provide features to organize, catalog, and document data assets within the data lake. They help establish data lineage, enable data discovery, and enforce compliance with data governance policies.

Data 52

Data Storage Construction Business Intelligence 52

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 75

Analytics DevOps Development Software Review 75

Altexsoft

OCTOBER 29, 2020

Here, we introduce you to ETL testing – checking that the data safely traveled from its source to its destination and guaranteeing its high quality before it enters your Business Intelligence reports. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

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.

Data 98

Data Technical Review Storage Systems Review 98

Cloudera

DECEMBER 7, 2017

That data may be used in ways that don’t comply with appropriate security and governance policies. That data may be hard to discover for other users and other applications. That data may be hard to track for audit and compliance purposes. There is a better way.

Data 40

Data Artificial Inteligence Machine Learning Analytics 40

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 82

Data Analytics Cloud Technical Review 82

Cloudera

OCTOBER 25, 2022

“They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”. It allows users to rapidly ingest data and run self-service analytics and machine learning. Compliance monitoring and incident response. Data loss prevention.

Cloud 52

Cloud Data Firewall AWS 52

Altexsoft

NOVEMBER 9, 2021

Whether a new or existing contract, it has to be thoroughly reviewed to ensure clear, unambiguous phrasing of all clauses and variations, compliance to current regulations, absence of hidden risks, pitfalls, or fees, and so on. Compliance evaluation. Invoice and payment analytics to detect errors, compliance issues, and fraud.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Openxcell

JANUARY 3, 2025

Openxcell is always ready to understand your project needs and use AI’s full potential to deliver a solution that propels your business forward. The company offers a wide range of AI Development services, such as Generative AI services, Custom LLM development , AI App Development , Data Engineering , GPT Integration , and more.

Artificial Inteligence 40

Artificial Inteligence Company Development Artificial Intelligence 40

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

JULY 19, 2022

It’s often used by internal apps managing business processes — ERPs, accounting software, and medical practice management systems , to name just a few. The analytical plane embraces data that is collected and transformed for analytical purposes such as enterprise reporting, business intelligence , data science , etc.

Architecture 52

Architecture Data Analytics Data Engineering 52

Capgemini

NOVEMBER 14, 2022

Data has to be easy to find, understand, access, and use for everyone in the chain: data engineers, analysts, data scientists, and business users. It makes the data more accessible and understandable to everyone, especially less-skilled data consumers.

Agile 52

Agile Technical Review Systems Review Culture 52

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. A mart is a group of aggregated tables (e.g.,

System Design 52

System Design Systems Review System Data 52

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.

Architecture 52

Architecture Data Storage Artificial Inteligence 52

Datavail

MARCH 10, 2022

Data stewards – provide oversight of data sets to maintain data integrity and ensure implementation of policies from the committee and end-user compliance with the policies. Others – data modelers, data engineers, data architects, and data quality analysts also contribute to the DG process.

Government 40

Government Strategy Weak Development Team Company 40

Altexsoft

SEPTEMBER 9, 2022

Efficient metadata management ensures data integrity , consistency, trustworthiness, and compliance. To ensure metadata quality as well as correct application of metadata policies and proper compliance to requirements and standards, audits have to be regularly conducted by data stewards. Risk management and compliance.

Tools 59

Tools Technical Review Software Review Systems Review 59

Abhishek Tiwari

JULY 20, 2019

ERP engineering squad - supply chain planning, purchase order management, product lifecycle management, merchandise planning, etc. Back-office engineering squad - customer support, business intelligence, real-estate management, systems for finance & HR, etc.

Engineering 61

Engineering Weak Development Team Software Review Technical Review 61

TIBCO - Connected Intelligence

DECEMBER 20, 2021

TIBCO DQ will become the new data quality product family, through an evolution of our current data quality offerings, significantly enhancing current capabilities available throughout the TIBCO data fabric with built-in AI and ML to automate quality, detection, monitoring, and anomaly resolution.

Innovation 26

Innovation Analytics Virtualization Cloud 26

AWS Machine Learning - AI

JULY 10, 2024

Amazon Q can also help employees do more with the vast troves of data and information contained in their company’s documents, systems, and applications by answering questions, providing summaries, generating business intelligence (BI) dashboards and reports, and even generating applications that automate key tasks.

Artificial Inteligence 127

Artificial Inteligence AWS Generative AI Knowledge Base 127

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 52

Big Data Analytics Data Analysis 52

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 64

Weak Development Team Artificial Inteligence Machine Learning Software Review 64

Altexsoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. This means that companies don’t necessarily need a large data engineering team. Data democratization. Data use component in a modern data stack.

Data 59

Data Technical Review Software Review Open Source 59

Cloudera

MARCH 2, 2021

However, in the typical enterprise, only a small team has the core skills needed to gain access and create value from streams of data. This data engineering skillset typically consists of Java or Scala programming skills mated with deep DevOps acumen. A rare breed. What do you mean by democratizing?

Data 112

Data Weak Development Team Data Engineering Enterprise 112

AWS Machine Learning - AI

APRIL 3, 2025

Embracing generative AI with Amazon Bedrock The company has identified several use cases where generative AI can significantly impact operations, particularly in analytics and business intelligence (BI). This tool democratizes data access across the organization, enabling even nontechnical users to gain valuable insights.

AWS 69

AWS Generative AI Artificial Inteligence Data 69