Apiumhub

NOVEMBER 17, 2022

It is an excellent opportunity for tech leaders, developers, architects, and business innovation leaders to learn about the latest tech trends, get informed, and meet like-minded people in the industry. Jesse Anderson – Data Engineer, Creative Engineer, and Managing Director of Big Data Institute.

Technical Review 81

Technical Review Software Review Fractional CTO CTO Coach 81

Apiumhub

JUNE 22, 2021

Data Innovation Summit topics. Same as last year, the event offers six workshops (crash-course) themes, each dedicated to a unique domain area: Data-driven Strategy, Analytics & Visualisation, Machine Learning, IoT Analytics & Data Management, Data Management and Data Engineering.

Innovation 84

Innovation Data Technical Review Artificial Inteligence 84

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.

Engineering 52

Engineering Data Storage AWS 52

Altexsoft

MARCH 16, 2021

In this article, we will explain the concept and usage of Big Data in the healthcare industry and talk about its sources, applications, and implementation challenges. What is Big Data and its sources in healthcare? So, what is Big Data, and what actually makes it Big? Let’s see where it can come from.

Big Data 116

Big Data Healthcare Applications Data 116

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Erik Bernhardsson

OCTOBER 27, 2015

I was featured in Peadar Coyle’s interview series interviewing various “data scientists” – which is kind of arguable since (a) all the other ppl in that series are much cooler than me (b) I’m not really a data scientist. So I think for anyone who wants to build cool ML algos, they should also learn backend and data engineering.

Data 100

Data Big Data Machine Learning Artificial Inteligence 100

Mobilunity

DECEMBER 21, 2022

Data scientists specialize in a variety of tasks that can benefit businesses in different ways. Some of the most noteworthy services they offer include: Data Science and Big Data Consulting. Big data engineer experts review existing data architecture, explore data sources, and analyze data lakes.

Data 52

Data How To Machine Learning Artificial Inteligence 52

Apiumhub

APRIL 1, 2021

Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by by EMC Education Services. The whole data analytics lifecycle is explained in detail along with case study and appealing visuals so that you can see the practical working of the entire system.

Artificial Inteligence 52

Artificial Inteligence Data Handbook Machine Learning 52

Altexsoft

APRIL 13, 2023

Leading executives focus on building resilient and intelligent supply chains that can withstand the turmoil due to data-based proactive decisions. According to the PwC 2023 Digital Trends in Supply Chain Survey , 86 percent of respondents believe they should invest more in technology to identify, track, and measure supply chain risk.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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.

Big Data 78

Big Data Analytics Tools Applications 78

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?

Big Data 98

Big Data Tools Data Storage 98

Altexsoft

SEPTEMBER 9, 2022

In data science , metadata is one of the central aspects: It describes data (including unstructured data streams) fed into a big data analytical platform, capturing, for example, formats, file sizes, source of information, permission details, etc. Types of metadata. There are multiple ways to categorize metadata.

Tools 59

Tools Technical Review Software Review Systems Review 59

CIO

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

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Data Artificial Inteligence Technical Advisors Technical Review 350

Datavail

JUNE 8, 2023

Data Summit 2023 was filled with thought-provoking sessions and presentations that explored the ever-evolving world of data. From the technical possibilities and challenges of new and emerging technologies to using Big Data for business intelligence, analytics, and other business strategies, this event had something for everyone.

Database Administration 52

Database Administration Data Artificial Inteligence Analytics 52

Abhishek Tiwari

DECEMBER 27, 2017

There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole. Unified data management architecture. Based on data access pattern i.e. hot, warm and cold Alluxio makes.

Trends 49

Trends Artificial Inteligence Data Big Data 49

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

AUGUST 22, 2022

What’s more, Gartner identifies data fabric implementation as one of the top strategic technology trends for 2022 and expects that by 2024, data fabric deployments will increase the efficiency of data use while halving human-driven data management tasks. What is data fabric? Data fabric architecture example.

Architecture 52

Architecture Artificial Inteligence Technical Review Data 52

Altexsoft

FEBRUARY 8, 2021

And planning, in turn, relies on understanding of current performance, past trends, existing risks, and possible future scenarios. There are two main approaches to demand planning: Traditional statistical methods make forecasts based on historical data and assume the continuation of existing trends. Stock management.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

O'Reilly Media - Ideas

MARCH 6, 2019

Spotlight on Innovation: AI Trends with Roger Chen , March 13. Artificial Intelligence for Big Data , April 15-16. Data science and data tools. Practical Linux Command Line for Data Engineers and Analysts , March 13. Data Modelling with Qlik Sense , March 19-20. AI and machine learning.

Course 10

Course Artificial Inteligence Training Microservices 10

Apiumhub

APRIL 5, 2022

M2- Data Engineering Stage: Technical track focusing on agile approaches to designing, implementing and maintaining a distributed data architecture to support a wide range of tools and frameworks in production. Presentations by some of the leading experts, researchers and practitioners in the area.

Innovation 52

Innovation Data Artificial Inteligence Case Study 52

CIO

AUGUST 5, 2022

Data visualization definition. Data visualization is the presentation of data in a graphical format such as a plot, graph, or map to make it easier for decision makers to see and understand trends, outliers, and patterns in data. Maps and charts were among the earliest forms of data visualization.

Data 358

Data Analytics Travel Business Intelligence 358

Cloudera

DECEMBER 14, 2020

One trend that we’ve seen this year, is that enterprises are leveraging streaming data as a way to traverse through unplanned disruptions, as a way to make the best business decisions for their stakeholders. . Today, a new modern data platform is here to transform how businesses take advantage of real-time analytics.

Analytics 68

Analytics Big Data Government Cloud 68

BPM

JANUARY 18, 2019

Now we’re seeing AI dominating the conversations (without a lot of actual adoption in the early majority), and RPA creating a lot of buzz, though companies adopting it are starting to realize that scaling an RPA based automation architecture is flawed by design. This requires a new architecture capable of true scale and speed.

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Altexsoft

FEBRUARY 22, 2022

Predictive maintenance (PdM) involves constant monitoring of your equipment condition and conducting repairs only when bad trends are detected – but before breakdowns occur. Reporting and analytics is essential to obtain a bird eye view of your fleet and make data-based decisions. Processing data.

Software Review 52

Software Review Technical Review Software Technology 52

Cloudera

NOVEMBER 2, 2020

Correlations across data domains, even if they are not traditionally stored together (e.g. real-time customer event data alongside CRM data; network sensor data alongside marketing campaign management data). The extreme scale of “big data”, but with the feel and semantics of “small data”.

Data 90

Data Analytics Storage Big Data 90

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

CTOvision

FEBRUARY 12, 2015

Simply view your data as a graphic and use your own talents to interpret what they could mean. Any data can be explored, from Excel spreadsheets to Hadoop big data. It’s built on breakthrough technology that translates pictures of data into optimized database queries. It’s up to you and your data. --.

Software 110

Software Data Analysis Big Data 110

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Cloudera

JUNE 4, 2018

Aspire , built by Search Technologies , part of Accenture is a search engine independent content processing framework for handling unstructured data. It provides a powerful solution for data preparation and publishing human-generated content to search engines and big data applications. compliance reporting.

Pharmaceuticals 45

Pharmaceuticals Data Big Data Systems Review 45

Altexsoft

NOVEMBER 9, 2021

Traditional statistical methods use mainly internal, historical data to predict trends within relatively stable markets. Meanwhile, we’ll describe the process of turning raw data around you into actionable insights. But before we dive in, consider reading about data engineering to get an idea of the main concepts and stages.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Cloudera

AUGUST 24, 2020

Today we are continuing our discussion with Martin Mannion , EMEA Big Data Community lead at Deloitte and Paul Mackay, the EMEA Cloud Lead at Cloudera to look at why security and governance requirements must be tackled in the early stages of data-led use case development, thereby mitigating more work later on.

Cloud 75

Cloud Data Government Innovation 75

Cloudera

FEBRUARY 11, 2019

To achieve their goals of digital transformation and becoming data-driven, companies need more than just a better data warehouse or BI tool. They need a range of analytical capabilities from data engineering to data warehousing to operational databases and data science. Governing for compliance.

Government 56

Government Compliance Machine Learning Artificial Inteligence 56

Altexsoft

OCTOBER 26, 2022

Today, the CIO’s focus is primarily on a company’s IT architecture and infrastructure. Things like business knowledge, in-depth understanding of digital structures, experience in project management, and comprehensive know-how in areas such as big data, blockchain, AI, IoT, etc. CDO hard skills and qualifications.

CTO 52

CTO Organization Technical Review Culture 52

Altexsoft

DECEMBER 9, 2020

Diagnostic analytics identifies patterns and dependencies in available data, explaining why something happened. Predictive analytics creates probable forecasts of what will happen in the future, using machine learning techniques to operate big data volumes. Often, no technologies are involved in data analysis.

Analytics 102

Analytics Technical Review Technology Applications 102

Altexsoft

OCTOBER 3, 2019

Mark Huselid and Dana Minbaeva in Big Data and HRM call these measures the understanding of the workforce quality. One of the use cases for predictive analytics in HRM that Deloitte briefly described in the 2016 Global Human Capital Trends report was prediction of unscheduled absences. Tools for data integration.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Emerging trends 9.

Big Data 52

Big Data Analytics Data Analysis 52

O'Reilly Media - Ideas

JANUARY 25, 2022

What are the bigger changes shaping the future of software development and software architecture? Users certainly can search for content that doesn’t exist, so searches can be a good leading indicator of technology trends. It includes almost everything, from programming languages to cloud to architecture and more.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109