Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

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CTOvision

JULY 23, 2014

Enterprises everywhere have been seeking improved ways to make use of their data. Wherever your organization falls on the spectrum, odds are very likely that you have established requirements for open framework and open repeatable solutions for your big data projects. With that spirit in mind, we produced a paper titled.

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Big Data Architecture Data Education 104

Datavail

AUGUST 4, 2022

‘Big Data’ is getting bigger. The second challenge requires sophisticated analysis programming that gleans the meaning of each data bit and attaches that to the meanings gleaned from other relevant data bits. Capturing Big Data – Managing the Volume. Capture, Clean, Conform.

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Altexsoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. 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.

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Kentik

SEPTEMBER 6, 2016

This post focuses on the first of those videos, in which Kentik’s Jim Frey, VP Strategic Alliances, talks about the complexity of today’s networks and how Big Data NetFlow analysis helps operators achieve timely insight into their traffic. Why Big Data NetFlow Analysis? Big Data Architectural Considerations.

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Altexsoft

AUGUST 25, 2020

Big data can be quite a confusing concept to grasp. What to consider big data and what is not so big data? Big data is still data, of course. Big data is tons of mixed, unstructured information that keeps piling up at high speed. Data engineering vs big data engineering.

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CTOvision

JULY 9, 2014

The term “Big Data” has become synonymous with this evolution. But still, many of our customers continue to ask, “What is Big Data?”, “What are its use cases?”, What is Big Data? The data is too big, moves too fast, or does not fit the structures of your database architectures.

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Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

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CTOvision

NOVEMBER 10, 2014

Download “Examining New Mission-Enabling Design Patterns Made Possible By The Cloudera-Intel Partnership” EDH-Architecture-Implications-of-Cloudera-Intel-Partnership.pdf – Downloaded 83 times – 956 kB. Analysis Big Data CTO Cyber Security DoD and IC'

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CTOvision

AUGUST 18, 2014

Enterprises everywhere have been seeking improved ways to make use of their data. Wherever your organization falls on the spectrum, odds are very likely that you have established requirements for open framework and open repeatable solutions for your big data projects. With that spirit in mind, we produced a paper titled.

Big Data 115

Big Data Data Architecture Analysis 115

Mobilunity

AUGUST 3, 2021

Big Data is a collection of data that is large in volume but still growing exponentially over time. It is so large in size and complexity that no traditional data management tools can store or manage it effectively. While Big Data has come far, its use is still growing and being explored.

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CTOvision

AUGUST 25, 2014

Leading organizations are changing the way they think about data with an enterprise data hub and driving everyday decisions and actions, from fraud prevention to insider threat analysis to exploratory analytics, with new information and new insights. The following is from Cloudera: Bring More Analysis to Your Data.

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CTOvision

OCTOBER 26, 2015

I'm currently researching big data project management in order to better understand what makes big data projects different from other tech related projects. So far I've interviewed more than a dozen government, private sector, and academic professionals, all of them experienced in managing data intensive projects.

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CTOvision

JUNE 9, 2014

The graphic was produced by three of the most highly regarded practitioners of real world data solutions I know, with contributions and mentorship of by one of the nation’s great enterprise architects. Download “Do You Know Big Data?” Do You Know Big Data? (74 74 downloads).

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CTOvision

SEPTEMBER 21, 2015

Here’s something to think about when you're planning a big data project: are you planning a project or a program ? Relatively self-contained big data projects may be tied to an ongoing process or program that is already developing or delivering a product or service. A program is something ongoing and relatively permanent.

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CTOvision

MAY 23, 2014

We previously wrote about the Pentaho Big Data Blueprints series, which include design packages of use to enterprise architects and other technologists seeking operational concepts and repeatable designs. Save data costs and boost analytics performance. An intuitive graphical, no-coding big data integration.

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KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies. User data collection is data about a user who is collected for market research purposes.

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Big Data Data Development Business Intelligence 52

Apiumhub

OCTOBER 18, 2022

On October 3-4 we organized and hosted the Global Software Architecture Summit in Barcelona. This year the event was focused on Software Architecture Metrics as they are key to the maintainability and architectural quality of a software project. Attendees Profiles.

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CTOvision

MARCH 31, 2014

The Pentaho blog has just announced a series of design overviews which can be of use in accelerating data modernization activities in your enterprise. These Blueprints to Big Data Success include design packages around the use cases of: Optimizing the data warehouse. Streamlining the data refinery. By Bob Gourley.

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CTOvision

MAY 30, 2014

As part of its commitment to move up the value chain, DigitalGlobe is investing in ways to extract information from its imagery at scale and fuse that with other sources of geospatial data to deliver actionable intelligence for what it calls “show me there” and “show me where” questions. This negates challenges in data logistics.

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CTOvision

APRIL 9, 2015

on 21 May at 1pm, CTOvision publisher Bob Gourley will host a webinar SAS engineers in an overview of architectural best practices for SAS and Hadoop. This webinar will examine lessons learned, best practices and concepts of operation designed to help you make the most of your data. By Bob Gourley.

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Data Virtualization

OCTOBER 5, 2022

Reading Time: 3 minutes At the heart of every organization lies a data architecture, determining how data is accessed, organized, and used. For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

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Architecture Data Virtualization Analysis 52

CTOvision

NOVEMBER 10, 2014

On Thursday 11 December 2014, join noted enterprise CTO and publisher of CTOvision Bob Gourley and Cloudera’s lead systems architect in an examination of an architectural exemplar and repeatable design patterns you can use to enhance your use of data. Enhance security. Serve and support multiple workloads.

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Big Data Open Source Data Architecture 108

AWS Machine Learning - AI

FEBRUARY 26, 2024

Large Language Models (LLMs) have revolutionized the field of natural language processing (NLP), improving tasks such as language translation, text summarization, and sentiment analysis. A modular architecture, where each module can intake model inference data and produce its own metrics, is necessary.

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CTOvision

NOVEMBER 21, 2014

Director of Technology Solutions Webster Mudge in an examination of an architectural exemplar and repeatable design patterns you can use to enhance your use of data. The event will include an architectural exemplar that will show you how design patterns can be applied to real world designs. Enhance security. Webster Mudge is Sr.

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CIO

AUGUST 9, 2022

But data engineers also need soft skills to communicate data trends to others in the organization and to help the business make use of the data it collects. Data engineers and data scientists often work closely together but serve very different functions. Data engineer vs. data architect.

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TechCrunch

JANUARY 2, 2022

Founded in 2016 by chief executive officer SeungTaek Oh, the startup has three data annotation tools: AIMMO DaaS, which manages sensor fusion data for autonomous vehicle corporations; AIMMO GtaaS, a turnkey-based platform for big data; and AIMMO Enterprises, launched in 2020, a web-based SaaS annotation labeling tool using cloud architecture.

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CTOvision

OCTOBER 13, 2014

Editor’s Note: Pentaho’s open approach and value added enterprise capabilities are making it a very popular framework for knitting together organizational data holdings. PentahoWorld Keynotes Unveil Big Data Orchestration Platform Instrumental to Data-Driven Future. Advanced Data Security in Hadoop.

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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. Who needs a data lake? An example of a data lake architecture.

Architecture 52

Architecture Data Storage Machine Learning 52

Netflix Tech

SEPTEMBER 10, 2019

After recreating the dataset, you can plot the raw numbers and perform custom analyses to understand the distribution of the data across test cells. With our new platform for experimentation analysis, it’s easy for scientists to perfectly recreate analyses on their laptops in a notebook. Getting Data with the Metrics Repo 2.

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Analysis Metrics Software Review Testing 86

CTOvision

FEBRUARY 17, 2015

of their open data platform including new features which will be of high interest to any enterprise with data (all enterprises!). From their press release: Pentaho to Deliver On Demand Big Data Analytics at Scale on Amazon Web Services and Cloudera. Big Data Analytics with Cloudera Impala. “As Pentaho 5.3:

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CTOvision

JULY 19, 2014

a leading independent research firm, invited to participate in its report, “The Forrester Wave™: Big Data Streaming Analytics Platforms, Q3 2014 1 ”. Streaming Analytics is at the core of our IBO offering and is the basis upon which companies can manage fast ‘Big Data’ and the increasing impact of the ‘Internet of Things’.”.

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Apiumhub

MARCH 9, 2021

In information technology, data architecture is composed of models, policies, rules or standards that govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations. Responsibilities of a Data Architect. What is Data Architecture.

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CTOvision

DECEMBER 5, 2014

Director of Technology Solutions Webster Mudge, and Intel Corporation’s Enterprise Technology Specialist Ed Herold in an examination of an architectural exemplar and repeatable design patterns you can use to enhance your use of data. Enhance security. Serve and support multiple workloads. For more and to register see: [link].

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Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. Temporal data and time-series analytics. Text and Language processing and analysis.

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Big Data Technology Tools Cloud 85

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Define data sources. Cost control. Quality management.

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