Altexsoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. What is a data lake? Data warehouse vs. data lake in a nutshell.

Architecture 52

Architecture Data Storage Machine Learning 52

CIO

JANUARY 6, 2023

But 86% of technology managers also said that it’s challenging to find skilled professionals in software and applications development, technology process automation, and cloud architecture and operations. Companies will have to be more competitive than ever to land the right talent in these high-demand areas.

LAN 358

LAN Systems Administration How To WAN 358

CIO

SEPTEMBER 2, 2022

Software engineers are one of the most sought-after roles in the US finance industry, with Dice citing a 28% growth in job postings from January to May. The most in-demand skills include DevOps, Java, Python, SQL, NoSQL, React, Google Cloud, Microsoft Azure, and AWS tools, among others. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

Software engineers are one of the most sought-after roles in the US finance industry, with Dice citing a 28% growth in job postings from January to May. The most in-demand skills include DevOps, Java, Python, SQL, NoSQL, React, Google Cloud, Microsoft Azure, and AWS tools, among others. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

JULY 18, 2023

The CIO’s biggest hiring challenge is clear: “There is simply not enough talent to go around,” says Scott duFour, global CIO of business payments company Fleetcor, for whom positions in areas such as AI, cloud architecture, and data science remain the toughest to fill.

Technical Advisors 220

Technical Advisors Artificial Inteligence Generative AI How To 220

Altexsoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is. Feel free to enjoy it.

Data 87

Data Data Engineering Big Data Architecture 87

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 81

Backup Cloud Architecture Resources 81

TechCrunch

JANUARY 26, 2022

Big data is at the heart of how a lot of applications, and a lot of business overall, works these days. And when it comes to big data troves, the priority for organizations is to have tools to manage them efficiently, and parse and analyse them effectively.

Analytics 218

Analytics Data Big Data Business Intelligence 218

InnovationM

APRIL 25, 2024

This typically involves saving the model weights and architecture in a compatible format, such as a TensorFlow SavedModel or PyTorch state dictionary. Optimized for AI and ML: S pecialized infrastructure and tooling for optimal performance. Scalability and Cost-Efficiency: Dynamically scale resources and optimize cost effectiveness.

Artificial Inteligence 52

Artificial Inteligence Serverless Scalability Resources 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.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

Netflix Tech

MARCH 5, 2019

While our engineering teams have and continue to build solutions to lighten this cognitive load (better guardrails, improved tooling, …), data and its derived products are critical elements to understanding, optimizing and abstracting our infrastructure. Give us a holler if you are interested in a thought exchange.

Infrastructure 73

Infrastructure Scalability Cloud Data 73

CTOvision

MAY 1, 2014

The senior engineer will also take a lead role in interfacing with customer groups to understand their needs and tailor reports to enable data-driven decisions across key business areas. The senior engineer will have a great deal of freedom in choosing the right tools for the job, and will have strong support in getting it right.

Big Data 107

Big Data Data Engineering Engineering Data Center 107

Cloudera

AUGUST 3, 2022

One approach is to use 3rd party tools (such as Privacera ) that integrate with Spark. However, it not only increases costs but requires duplication of policies and yet another external tool to manage. The customer also experienced equal or better performance with the simpler architecture in CDP. Starting with CDP 7.1.7

Policies 85

Policies Machine Learning Artificial Inteligence Data Engineering 85

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. Key components of an MLOps cycle.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

Altexsoft

SEPTEMBER 9, 2022

We’ll briefly recap the basics first and then discuss metadata management and tools that can come in handy. Metadata is basically information that describes other data. It helps us understand the origin, structure, nature, and context of data. So, there are specialized tools that automate metadata management.

Tools 59

Tools Technical Review Software Review Systems Review 59

Mentormate

JANUARY 11, 2022

Only the largest engineering organizations have the scale to make this kind of continuous investment. Human-Centered Design, Composable Architectures, and Citizen Builders. Custom and off-the-shelf microservices cover the complexity of security, scalability, and data isolation and integrate into complex workflows through orchestration.

Technical Review 98

Technical Review Trends Off-The-Shelf Software Review 98

Mobilunity

MAY 8, 2023

It is designed to store vast amounts of data from a variety of sources. Moreover an Enterprise Data Lake makes it accessible to data scientists, analysts, and other users across the enterprise. Ingestion zone is where data is collected from various sources and ingested into the data lake. Scalability.

Engineering 52

Engineering Data Storage AWS 52

Datavail

JUNE 20, 2023

Percona Live 2023 was an exciting open-source database event that brought together industry experts, database administrators, data engineers, and IT leadership. The sessions were filled with engaging conversations with all the open-source tool developers, meet-up organizers, consultants, entrepreneurs, experts, and renowned speakers.

Open Source 52

Open Source Database Administration Survey AWS 52

Trigent

AUGUST 26, 2022

Trigent offers end-to-end consulting services, design, development, and managed services across Infrastructure, Cloud, Mobility, BI, Analytics, Product Engineering, Quality Engineering, IoT, Data Engineering, and Artificial Intelligence.

Software Review 52

Software Review Software Technical Review Artificial Intelligence 52

CIO

FEBRUARY 13, 2023

Now, as more faculty, staff, and students are accessing information on-premises and in the cloud, IT has a borderless network and the team is implementing a zero-trust network architecture, says CIO Mugunth Vaithylingam. And it’s not just applications development where such tools are having an impact.

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Cloudera

JUNE 7, 2022

In our very own Enterprise Data Maturity research surveying over 3,000 IT and senior business leaders, we found that 40% of organizations are currently running hybrid but mostly on-premises, and 36% of respondents expect to shift to hybrid multi-cloud in the next 18 months. Where data flows, ideas follow.

Data 108

Data Architecture Analytics Government 108

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. Knowledge of Scala or R can also be advantageous.

Data Engineering 52

Data Engineering Fintech Engineering Data 52

Agile Engine

SEPTEMBER 29, 2023

Explore Data Studio projects and expertise in-depth Learn more Business challenge: addressing subscriber churn in the video streaming industry The client engaging our ML and data engineers is a premium streaming video on demand (SVOD) network top-listed by CNET in 2023.

Video 52

Video Machine Learning Artificial Inteligence Automotive 52

Capgemini

JANUARY 17, 2023

Facebook Twitter Linkedin As the year winds down, this is a good time to assess personal resolutions you have for the new year and, as a data leader, it’s also an opportunity to take a fresh look at your data and AI strategy. Here are four resolutions to make your data strategy pay off this year. Reassess your data architecture.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

Cloudera

JANUARY 19, 2022

We have been working hard to build our cloud-native data services on Cloudera Data Platform (CDP), which include CDP Data Warehouse, CDP Operational Database, CDP Machine Learning, CDP Data Engineering and CDP Data Flow. Download the reports to see the detailed scores .

Report 87

Report Technical Advisors Cloud Analytics 87

AWS Machine Learning - AI

JANUARY 26, 2024

Understanding and addressing LLM vulnerabilities, threats, and risks during the design and architecture phases helps teams focus on maximizing the economic and productivity benefits generative AI can bring. Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications.

Artificial Inteligence 119

Artificial Inteligence Generative AI Security Applications 119

Kentik

JANUARY 3, 2018

How will network monitoring tools evolve to accommodate this ever-changing IoT network landscape? Network analytics has the power to examine details of the IoT communications patterns made through various protocols and correlate these to data paths traversed throughout the network. Return query results against all this data in seconds.

IoT 40

IoT Network Tools Big Data 40

Cloudera

DECEMBER 21, 2020

Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Scientist. He seeks to quickly discover and learn about available data sets.

Data 97

Data Virtualization Banking Data Engineering 97

Confluent

JUNE 18, 2019

Software projects of all sizes and complexities have a common challenge: building a scalable solution for search. For this reason and others as well, many projects start using their database for everything, and over time they might move to a search engine like Elasticsearch or Solr. You might be wondering, is this a good solution?

Scalability 96

Scalability Architecture Machine Learning Artificial Inteligence 96

KitelyTech

FEBRUARY 3, 2021

Big data also helps to understand customer behavior by collecting information about users and their behaviors, which is important for online business development. Big data visualization tools can be used to explore relationships and patterns in big data. Therefore, the software must have an easily extendable architecture.

Big Data 52

Big Data Data Development Business Intelligence 52

Hu's Place - HitachiVantara

JUNE 5, 2019

You can’t sit back and let some one else make decisions for you about security, data definitions, and business rules and you can’t make these decisions in isolation. One of the key enablers for the DataOps process was Pentaho ’s data integration and pipeline orchestration. Fatima Hamad, Sr.

Technical Review 40

Technical Review Analytics Data Engineering Scalability 40

Cloudera

JANUARY 15, 2021

Cloudera Data Warehouse is a highly scalable service that marries the SQL engine technologies of Apache Impala and Apache Hive with cloud-native features to deliver best-in-class price-performance for users running data warehousing workloads in the cloud. Overview of Cloudera Data Warehouse. Benchmark Description.

Performance 92

Performance Cloud Data Storage 92

CIO

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 317

Analytics Data Engineering Machine Learning Artificial Inteligence 317

Mobilunity

DECEMBER 21, 2022

Tech companies use data science to enhance user experience, create personalized recommendation systems, develop innovative solutions, and more. Data science in agriculture can help businesses develop data pipelines specifically for automation and fast scalability. Data Modeling. Data Warehousing.

Data 52

Data How To Machine Learning Artificial Inteligence 52

Altexsoft

AUGUST 25, 2020

Big data is tons of mixed, unstructured information that keeps piling up at high speed. That’s why traditional data transportation methods can’t efficiently manage the big data flow. Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data.

Big Data 75

Big Data Data Engineering Engineering Data 75

O'Reilly Media - Ideas

JUNE 4, 2019

Data science and data tools. Business Data Analytics Using Python , June 25. Debugging Data Science , June 26. Programming with Data: Advanced Python and Pandas , July 9. Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12.

Course 67

Course Training Artificial Inteligence Software Review 67

O'Reilly Media - Ideas

JUNE 5, 2019

Data science and data tools. Business Data Analytics Using Python , June 25. Debugging Data Science , June 26. Programming with Data: Advanced Python and Pandas , July 9. Programming with Data: Advanced Python and Pandas , July 9. Understanding Data Science Algorithms in R: Regression , July 12.

Course 50

Course Training Artificial Inteligence Software Review 50