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. Many were still using spreadsheets or basic payroll software.

Recruiting 224

Recruiting Technical Review Software Review Systems Review 224

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

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

TechCrunch

OCTOBER 7, 2021

Every developer (the origin of our name) has a few basic needs, like clear documentation, help getting started and use cases to spark creativity. If your customers are data engineers, it probably won’t make sense to discuss front-end web technologies. Don’t just publish to check a box.

Weak Development Team 231

Weak Development Team Software Development Marketing Technical Advisors 231

Xebia

JANUARY 30, 2025

In this blog post, we want to tell you about our recent effort to do metadata-driven data masking in a way that is scalable, consistent and reproducible. Using dbt to define and document data classifications and Databricks to enforce dynamic masking, we ensure that access is controlled automatically based on metadata.

Data 130

Data Groups Data Engineering Systems Review 130

CIO

JANUARY 6, 2023

Database developers should have experience with NoSQL databases, Oracle Database, big data infrastructure, and big data engines such as Hadoop. It requires a strong ability for complex project management and to juggle design requirements while ensuring the final product is scalable, maintainable, and efficient.

LAN 215

LAN How To Systems Administration Software Engineering 215

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

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

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

CIO

DECEMBER 11, 2023

Capture patient documentation with a digital scribe. Digital solutions to implement generative AI in healthcare EXL, a leading data analytics and digital solutions company , has developed an AI platform that combines foundational generative AI models with our expertise in data engineering, AI solutions, and proprietary data sets.

Generative AI 113

Generative AI Artificial Inteligence Healthcare Artificial Intelligence 113

CIO

JULY 5, 2023

Among them are cybersecurity experts, technicians, people in legal, auditing or compliance, as well as those with a high degree of specialization in AI where data scientists and data engineers predominate. We must provide the necessary resources, both financial and human, to those projects with the most potential.”

Artificial Inteligence 158

Artificial Inteligence Energy Generative AI Strategic Planning 158

Altexsoft

JANUARY 14, 2021

The variety of data explodes and on-premises options fail to handle it. Apart from the lack of scalability and flexibility offered by modern databases, the traditional ones are costly to implement and maintain. At the moment, cloud-based data warehouse architectures provide the most effective employment of data warehousing resources.

Backup 115

Backup Azure Software Review Architecture 115

Cloudera

MAY 13, 2021

Importing data from one or multiple systems to apply transformations and then export results to another system is becoming increasingly common—which means these kinds of activities must become more automated and easily repetitive. When evaluating a stream processing engine, consider its processing abstraction capabilities.

Engineering 102

Engineering Comparison Open Source Scalability 102

Altexsoft

FEBRUARY 11, 2023

Data architect and other data science roles compared Data architect vs data engineer Data engineer is an IT specialist that develops, tests, and maintains data pipelines to bring together data from various sources and make it available for data scientists and other specialists.

Data 87

Data Data Engineering Big Data Architecture 87

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. . Learn more on how to use the feature from our public documentation. . Fine grained access control (FGAC) with Spark. Starting with CDP 7.1.7

Policies 90

Policies Artificial Inteligence Machine Learning Data Engineering 90

d2iq

MARCH 31, 2022

However, many organizations struggle moving from a prototype on a single machine to a scalable, production-grade deployment. Model Development Jupyter Notebooks makes documentation, data visualization, and caching a lot easier for data scientists.

Artificial Inteligence 69

Artificial Inteligence Machine Learning How To Artificial Intelligence 69

Cloudera

FEBRUARY 1, 2024

Day 0 — Design and Preparation: Focuses on designing and preparing for your installation, including gathering requirements, planning architecture, allocating resources, setting up network and security, and documentation creation. Network setup: configure the network infrastructure to ensure connectivity and data flow.

Backup 82

Backup Cloud Architecture Resources 82

Cloudera

AUGUST 15, 2024

This section enables users to select and display operational insights for specific services, such as Data Hub, Data Engineering, and Data Warehouse, providing immediate insights into their operations. Bringing these metrics to the homepage helps users monitor performance and make data-driven decisions more effectively.

Database Administration 74

Database Administration Analytics Metrics Innovation 74

Honeycomb

APRIL 23, 2025

Note that OpenTelemetry does not solve the problem of data gravity, because observability is about much more than just instrumentation. Changing vendors will also involve changing alerts, dashboards, bookmarks, runbooks, documentation, workflows, API calls, mental models, expertise, and more. These are, after all, data problems.

Weak Development Team 106

Weak Development Team Metrics Storage Engineering 106

d2iq

JANUARY 18, 2022

Security: Data privacy and security are often afterthoughts during the process of model creation but are critical in production. Kubeflow has its own challenges, too, including difficulties with installation and with integrating its loosely-coupled components, as well as poor documentation.

Artificial Inteligence 72

Artificial Inteligence Machine Learning AWS Weak Development Team 72

Cloudera

FEBRUARY 16, 2021

Cloudera Operational Database (COD) plays the crucial role of a data store in the enterprise data lifecycle. You can use COD with: Cloudera DataFlow to ingest and aggregate data from various sources. Cloudera Data Engineering to ingest bulk data and data from mainframes. Cloudera Data Engineering.

Artificial Inteligence 83

Artificial Inteligence Machine Learning Data Engineering Policies 83

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. Use cases: moving data from on-premises to cloud or between cloud environments.

Software Review 69

Software Review Software Data Technical Review 69

Cloudera

AUGUST 30, 2022

It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. Deploying modern data architectures.

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

Cloudera

APRIL 22, 2021

Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Data 101

Data Storage Architecture Big Data 101

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. Still, it’s the number one choice for data-driven companies, and here’re some reasons why. Scalability.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Cloudera

AUGUST 26, 2020

The Cloudera Connect Technology Certification program uses a well-documented process to test and certify our Independent Software Vendors’ (ISVs) integrations with our data platform. Informatica and Cloudera deliver a proven set of solutions for rapidly curating data into trusted information. Certified ISV Technology Partners.

Data 84

Data Artificial Inteligence Machine Learning Disaster Recovery 84

Invid Group

AUGUST 28, 2024

Automation and Scalability Operationalization normally involves automating processes and workflows to enable scalability and efficiency. By automating data processes, organizations can ensure that insights and models are consistently applied to new data and operational decisions, reducing manual effort and improving responsiveness.

Technical Review 52

Technical Review Artificial Inteligence Performance Azure 52

Apiumhub

NOVEMBER 17, 2022

Francesco Cesarini – Founder, & Technical Director at Erland Solutions, Co-author of “Erlang Programming“ and “Designing for Scalability with Erlang/OTP“. Jesse Anderson – Data Engineer, Creative Engineer, and Managing Director of Big Data Institute. Who Do You Trust? Beware of Your Brain!

Technical Review 81

Technical Review Software Review Fractional CTO CTO Coach 81

Altexsoft

SEPTEMBER 23, 2019

Business analyst is a member of a product development team who analyzes the business domain, documents its processes and systems, outlines business requirements, and matches a software business model with the software being built. Documentation and visualization master. Deliverable: documented business requirements.

Weak Development Team 62

Weak Development Team Software Development Project Management Research 62

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

O'Reilly Media - Data

MARCH 22, 2018

A human interpretable interpretation(HII) of the model’s decision policies may provide insightful information that could easily be shared among peers (analysts, managers, data scientists, data engineers). print ( "Explain the prediction, for the document: n " ). the API address. algorithmia_uri = "[link].

Off-The-Shelf 177

Off-The-Shelf Artificial Inteligence Machine Learning Weak Development Team 177

Capgemini

OCTOBER 10, 2024

But gathering, analyzing, documenting, and structuring requirements can be tedious, and the results are often laden with errors. The traditional process for gathering requirements and documentation is manual, which makes it time-consuming and prone to inaccuracies, omissions, and inconsistencies.  Thanks to Gemini 1.5

Artificial Inteligence 52

Artificial Inteligence Analysis Google Cloud Infrastructure 52

Cloudera

JULY 11, 2023

Apache Impala is a distributed C++ backed SQL engine that integrates with Kudu to serve BI results over millions of rows meeting sub-second service-level agreements. Cloudera offers Apache Kudu to run in Real Time DataMart Clusters , and Apache Impala to run in Kubernetes in the Cloudera Data Warehouse form factor.

Data 70

Data Virtualization Pharmaceuticals Storage 70

Cloudera

APRIL 15, 2021

13-16] with appropriate documentation. YARN new placement rules engine provides better conversions for fair scheduler to capacity scheduler migration and provides better placement rules management . Data Engineering . Hive Warehouse Connector (HWC) makes data engineering simpler and faster. Object Store.

Cloud 70

Cloud Data Engineering Resources Engineering 70

Perficient

APRIL 1, 2024

A better understand of these by visiting respective website is advisable for better understanding: Lakehouse: In layman terms, this is the storehouse which will store unstructured data like CSV files in folders and structured data i.e., table (in Delta lake format). as depicted in postman request screenshot.

Data 64

Data Azure Case Study Data Engineering 64

Cloudera

SEPTEMBER 28, 2021

In the next sections, we’ll walk through a simple data access scenario both without and with RAZ for two separate teams — the data scientists and the data engineers. Let’s say that both Jon and Remi belong to the Data Engineering group. Without RAZ: Group-based access control with IDBroker.

Groups 62

Groups Cloud Data AWS 62

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Data 63

Data Software Review Technical Review Microservices 63