Apiumhub

DECEMBER 9, 2024

Integrated Data Lake Synapse Analytics is closely integrated with Azure Data Lake Storage (ADLS), which provides a scalable storage layer for raw and structured data, enabling both batch and interactive analytics. When Should You Use Azure Synapse Analytics?

Azure 89

Azure Analytics Storage Artificial Inteligence 89

AWS Machine Learning - AI

MARCH 13, 2025

They assist with operations such as QA reporting, coaching, workflow automations, and root cause analysis. Amazon Bedrocks broad choice of FMs from leading AI companies, along with its scalability and security features, made it an ideal solution for MaestroQA. Now, they are able to detect compliance risks with almost 100% accuracy.

Generative AI 98

Generative AI CTO Coach AWS Artificial Inteligence 98

Altexsoft

AUGUST 25, 2020

That’s why a data specialist with big data skills is one of the most sought-after IT candidates. Data Engineering positions have grown by half and they typically require big data skills. Data engineering vs big data engineering. Big data processing. maintaining data pipeline.

Big Data 75

Big Data Data Engineering Engineering Data 75

TechCrunch

NOVEMBER 2, 2022

.” Built on top of data warehousing service Snowflake and Google’s BigQuery engine, Y42 ‘s new fully managed service aims to provide businesses with more of the tools to make their data stack easily accessible for more users while also providing additional collaboration tools and improved data governance services.

Data 203

Data Business Intelligence Open Source Government 203

AWS Machine Learning - AI

NOVEMBER 15, 2024

Additional integrations with services like Amazon Data Firehose , AWS Glue , and Amazon Athena allowed for historical reporting, user activity analytics, and sentiment trends over time through Amazon QuickSight. All AWS services are high-performing, secure, scalable, and purpose-built.

Generative AI 112

Generative AI AWS Groups Artificial Inteligence 112

TechCrunch

JULY 25, 2022

The company was founded in 2021 by Brian Ip, a former Goldman Sachs executive, and data engineer YC Chan. He added that this disadvantage of payroll software is that they only provide basic admin functions around payroll calculation, and are not scalable.

Recruiting 224

Recruiting Technical Review Software Review Systems Review 224

CIO

SEPTEMBER 2, 2022

Software engineers are at the forefront of digital transformation in the financial services industry by helping companies automate processes, release scalable applications, and keep on top of emerging technology trends. Full-stack software engineer. Back-end software engineer. Director of software engineering.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

AUGUST 31, 2022

Software engineers are at the forefront of digital transformation in the financial services industry by helping companies automate processes, release scalable applications, and keep on top of emerging technology trends. Full-stack software engineer. Back-end software engineer. Director of software engineering.

Software Engineering 148

Software Engineering Data Engineering DevOps AWS 148

CIO

FEBRUARY 14, 2023

A 2023 New Vantage Partners/Wavestone executive survey highlights how being data-driven is not getting any easier as many blue-chip companies still struggle to maximize ROI from their plunge into data and analytics and embrace a real data-driven culture: 19.3% report they have established a data culture 26.5%

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

TechCrunch

FEBRUARY 10, 2021

The San Francisco-based fintech offers a credit card aimed at helping first-time borrowers build credit history, based on their cash flow, rather than on their FICO or credit report ratings. Tomo Credit feels to me like it is tackling this in a hugely scalable, mainstream way.”.

Weak Development Team 253

Weak Development Team Banking Fintech Data Engineering 253

Cloudera

JANUARY 19, 2022

Gartner® recognized Cloudera in three recent reports – Magic Quadrant for Cloud Database Management Systems (DBMS), Critical Capabilities for Cloud Database Management Systems for Analytical Use Cases and Critical Capabilities for Cloud Database Management Systems for Operational Use Cases. Download the reports to see the detailed scores .

Report 90

Report Cloud Technical Advisors Analytics 90

CIO

APRIL 27, 2023

The past year was rough for the tech industry, with several companies reporting layoffs and the looming threat of a recession. For technologists with the right skills and expertise, the demand for talent remains and businesses continue to invest in technical skills such as data analytics, security, and cloud. as of January.

Technical Review 174

Technical Review Software Review Systems Review Software Engineering 174

Perficient

FEBRUARY 13, 2025

Breaking down silos has been a drumbeat of data professionals since Hadoop, but this SAP <-> Databricks initiative may help to solve one of the more intractable data engineering problems out there. SAP has a large, critical data footprint in many large enterprises. However, SAP has an opaque data model.

Government 64

Government Open Source Artificial Inteligence Machine Learning 64

CIO

JANUARY 6, 2023

For some that means getting a head start in filling this year’s most in-demand roles, which range from data-focused to security-related positions, according to Robert Half Technology’s 2023 IT salary report. Recruiting in the tech industry remains strong, according to the report.

LAN 215

LAN Systems Administration How To Software Engineering 215

Perficient

MARCH 27, 2025

Ensuring compliant data deletion is a critical challenge for data engineering teams, especially in industries like healthcare, finance, and government. Deletion Vectors in Delta Live Tables offer an efficient and scalable way to handle record deletion without requiring expensive file rewrites. What Are Deletion Vectors?

Compliance 64

Compliance Systems Review Policies Storage 64

Cloudera

OCTOBER 13, 2020

At the heart of CDP is SDX , a unified context layer for governance and security, that makes it easy to create a secure data lake and run workloads that address all stages of your data lifecycle (collect, enrich, report, serve and predict). Enrich – Data Engineering (Apache Spark and Apache Hive).

Cloud 97

Cloud Artificial Inteligence Machine Learning Data Engineering 97

Mobilunity

MAY 3, 2024

When it comes to financial technology, data engineers are the most important architects. As fintech continues to change the way standard financial services are done, the data engineer’s job becomes more and more important in shaping the future of the industry.

Data Engineering 52

Data Engineering Fintech Engineering Data 52

CIO

OCTOBER 18, 2023

To do so, the team had to overcome three major challenges: scalability, quality and proactive monitoring, and accuracy. The solution needed to scale to all of Fresenius’s dialysis centers, with each location sending 10MBps of treatment data at peak times.

Artificial Inteligence 200

Artificial Inteligence Analytics Machine Learning Artificial Intelligence 200

Xebia

JULY 29, 2024

Data Modelers: They design and create conceptual, logical, and physical data models that organize and structure data for best performance, scalability, and ease of access. In the 1990s, data modeling was a specialized role. Data Users: These are analysts and BI developers who use data within the organization.

Technical Review 130

Technical Review Data Systems Review Meeting 130

Capgemini

NOVEMBER 21, 2024

But, more practically, data and BI modernization are the creation of a data foundation of secure, trusted, and democratized data to support AI and analytics at scale. This is a critical consideration as many organizations face data-estate hurdles. To read the full whitepaper, click here.

Data 52

Data Government Innovation Architecture 52

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.

Data 112

Data Weak Development Team Data Engineering Enterprise 112

CIO

FEBRUARY 13, 2023

That also requires investing more in cloud infrastructure for storage and compute power resources so data scientists can process data, understand it, and be able to translate it “for benefits at the bedside,’’ Fleischut says. growth,’’ the firm wrote in a newly-published report on worldwide IT spending in Q4 22.

Budget 218

Budget Artificial Inteligence Technical Review VR 218

John Snow Labs

FEBRUARY 12, 2025

John Snow Labs’ Medical Language Models library is an excellent choice for leveraging the power of large language models (LLM) and natural language processing (NLP) in Azure Fabric due to its seamless integration, scalability, and state-of-the-art accuracy on medical tasks.

Artificial Inteligence 52

Artificial Inteligence Azure Healthcare Software Review 52

Altexsoft

JUNE 29, 2021

MLEs are usually a part of a data science team which includes data engineers , data architects, data and business analysts, and data scientists. Who does what in a data science team. Machine learning engineers are relatively new to data-driven companies.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

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. Let’s take a common use-case for Business Intelligence reporting. Figure 2: Example BI reporting data pipeline.

Data 115

Data Open Source Analytics Artificial Inteligence 115

Altexsoft

JANUARY 14, 2021

A data warehouse is often abbreviated as DW or DWH. You may also find it under the name of an enterprise data warehouse (EDW). It is usually created and used primarily for data reporting and analysis purposes. As such, it is possible to retrieve old archived data if needed. Data warehouse architecture.

Backup 115

Backup Azure Software Review Architecture 115

Mentormate

JANUARY 11, 2022

Custom and off-the-shelf microservices cover the complexity of security, scalability, and data isolation and integrate into complex workflows through orchestration. That lack of support leaves the citizen report builders and data scientists with no way to act on that data.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

CIO

JUNE 14, 2023

This can be achieved by utilizing dense storage nodes and implementing fault tolerance and resiliency measures for managing such a large amount of data. Focus on scalability. First and foremost, you need to focus on the scalability of analytics capabilities, while also considering the economics, security, and governance implications.

Data 97

Data Scalability Storage Big Data 97

Cloudera

NOVEMBER 19, 2020

government loses nearly 150 billion dollars due to potential fraud each year, McKinsey & Company reports. In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud. Some experts estimate the U.S.

Government 119

Government Artificial Inteligence Data Machine Learning 119

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 103

Games Artificial Inteligence Data Artificial Intelligence 103

Cloudera

AUGUST 3, 2022

This limited usage of Spark at security-conscious customers, as they were unable to leverage its rich APIs such as SparkSQL and Dataframe constructs to build complex and scalable pipelines. . One customer reported that they have adopted HWC secure access mode without much code refactoring from HWC LLAP execution mode. What’s Next.

Policies 90

Policies Artificial Inteligence Machine Learning Data Engineering 90

Netflix Tech

MARCH 25, 2019

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

Infrastructure 90

Infrastructure Data Technical Review Systems Review 90

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Architecture 102

Architecture Innovation Data Open Source 102

Cloudera

SEPTEMBER 23, 2021

Likewise, slow data speeds don’t win over customers or colleagues in the real-time business world. Microsoft’s own research once reported that a person visiting a website on a connected device is likely to wait no more than 10 seconds to see it before moving to a competitor’s site. When Data Accelerates.

Data 82

Data Sport Report Data Engineering 82

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 ). We selected change data capture as our first use case on Iceberg.

Data 88

Data Analytics Artificial Inteligence Machine Learning 88

Perficient

FEBRUARY 28, 2023

In the first article in this series, I explained the five components necessary to prevent a Data Lake from Becoming a Data Swamp. Data lakes work on the concept of load first and use later, which means the data stored in the repository doesn’t necessarily have to be used immediately for a specific purpose.

Data 110

Data Analytics Google Cloud Cloud 110

d2iq

JANUARY 18, 2022

Security: Data privacy and security are often afterthoughts during the process of model creation but are critical in production. Kubernetes would seem to be an ideal way to address some of the obstacles to getting AI/ML workloads into production.

Artificial Inteligence 72

Artificial Inteligence Machine Learning AWS Weak Development Team 72