Hacker Earth Developers Blog

JUNE 26, 2019

One should have a good understanding of basic programming concepts, data structures such as trees and graphs and most commonly used algorithms. The candidate should be able to code in either of the languages – Python or R-which are the most widely used languages in data science in the industry. Business /Domain Knowledge.

Data 200

Data How To Machine Learning Artificial Inteligence 200

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. The post The Future of the Data Lakehouse – Open appeared first on Cloudera Blog.

Data 96

Data Analytics Open Source Architecture 96

Hacker Earth Developers Blog

JUNE 26, 2019

One should have a good understanding of basic programming concepts, data structures such as trees and graphs and most commonly used algorithms. The candidate should be able to code in either of the languages – Python or R-which are the most widely used languages in data science in the industry. Business /Domain Knowledge.

Data 100

Data How To Machine Learning Artificial Inteligence 100

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

Capgemini

NOVEMBER 14, 2022

Data has to be easy to find, understand, access, and use for everyone in the chain: data engineers, analysts, data scientists, and business users. It makes the data more accessible and understandable to everyone, especially less-skilled data consumers. We have received your form submission.

Agile 52

Agile Technical Review Systems Review Culture 52

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

FEBRUARY 8, 2021

Supply chain practitioners and CEOs surveyed by 6river share that the main challenges of the industry are: keeping up with the rapidly changing customer demand, dealing with delays and disruptions, inefficient planning, lack of automation, rising costs (of transportation, labor, etc.),

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Migration of historical data from EDW Platform.

Data 85

Data Analytics Cloud Technical Review 85

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.

Big Data 59

Big Data Data Google Cloud Open Source 59

Altexsoft

JUNE 14, 2021

On top of that, the company uses big data analytics to quantify losses and predict risks by placing the client into a risk group and quoting a relevant premium. You can start investing in data infrastructure and analytical pipelines to automate data collection and analysis mechanisms. Customer data is heavily regulated.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

Altexsoft

APRIL 13, 2023

You can read the details on them in the linked articles, but in short, data warehouses are mostly used to store structured data and enable business intelligence , while data lakes support all types of data and fuel big data analytics and machine learning. Data siloes.

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

Cloudera

JANUARY 3, 2018

In a big data world, we often see three new roles emerge and work more closely together: data engineers, data scientists and architects. The data engineering team is a strategic necessity as data itself is more agile. You can think of them as the data workhorse.

Big Data 40

Big Data Data Data Engineering Engineering 40

Altexsoft

AUGUST 19, 2022

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Users can easily create a wide range of data-intensive, yet intelligible reports and dashboards and share obtained insights. What is Power used for?

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

JANUARY 22, 2020

Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. A complete guide to business intelligence and analytics. The role of business intelligence developer.

Analytics 20

Analytics Data IoT Analysis 20

AWS Machine Learning - AI

SEPTEMBER 3, 2024

Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. From deriving insights to powering generative artificial intelligence (AI) -driven applications, the ability to efficiently process and analyze large datasets is a vital capability.

Serverless 90

Serverless AWS Artificial Inteligence Big Data 90

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.

Data 349

Data Technical Advisors Artificial Inteligence Technical Review 349

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

TechCrunch

JUNE 17, 2021

” The tool Airbnb built was Minerva , optimised specifically for the kinds of questions Airbnb might typically have for its own data. And third of all, to provide customers with APIs that they can use to embed the metric-extracting tools into other applications, whether in business intelligence or elsewhere.

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Metrics Tools Data Big Data 247

ParkMyCloud

MAY 29, 2019

There is exponential growth in the cloud computing industry, so it’s no surprise that the demand for cloud computing intellect and skills is also increasing, with no slowing down in the foreseeable future. Business Intelligence Analyst. IoT Engineer. Here are some trends we’re seeing. Cloud Consultants.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Cloudera

NOVEMBER 19, 2020

Furthermore, the same tools that empower cybercrime can drive fraudulent use of public-sector data as well as fraudulent access to government systems. In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud.

Government 121

Government Artificial Inteligence Machine Learning Data 121

Altexsoft

AUGUST 21, 2019

Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data. Using specific tools and practices, businesses implement these methods to generate valuable insights. Data engineer. Data scientists.

Development 44

Development Software Engineering Data Engineering Architecture 44

Altexsoft

FEBRUARY 22, 2022

In a broader sense, it can also be called a computerized maintenance management system or CMMS (the difference is that a CMMS can be used in other industries as well). Integration with inventory management software is necessary in case you hold a big stock of parts and equipment and want to be in control. Processing data.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

OCTOBER 8, 2021

But more often than not data is scattered across a myriad of disparate platforms, databases, and file systems. What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. Comparison of data integration tools. ODI interface editor. Source: Oracle.

Tools 52

Tools Data Software Review Open Source 52

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.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

Altexsoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Data lake architecture example. Poor data quality, reliability, and integrity.

Architecture 52

Architecture Data Storage Machine Learning 52

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. A subscriber is a receiving program such as an end-user app or business intelligence tool.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Open Source 93

Altexsoft

JANUARY 14, 2021

It is usually created and used primarily for data reporting and analysis purposes. Thanks to the capability of data warehouses to get all data in one place, they serve as a valuable business intelligence (BI) tool, helping companies gain business insights and map out future strategies.

Backup 115

Backup Azure Software Review Architecture 115

Altexsoft

NOVEMBER 9, 2021

Traditionally, analytics is associated with business intelligence and data visualization that are focused on studying past events and current processes. Also known as predictive analytics, it’s about discovering hidden patterns and dependencies, forecasting future events, and supporting decisions with data. Extract data.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

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 Big Data 8

Altexsoft

DECEMBER 14, 2022

Then came standardized intermodal containers that revolutionized the transportation industry. If you are a programmer, a DevOps , a data engineer , or any other specialist who wants to use Docker in projects, you should have a clear roadmap of how to get started with this technology. Dockers working in London, England.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

OCTOBER 3, 2019

Mark Huselid and Dana Minbaeva in Big Data and HRM call these measures the understanding of the workforce quality. In 2016, the company attrition rates were 4 percent higher over the industry benchmark. The platform provides “ business intelligence, planning, and predictive capabilities within one product” and uses AI and ML.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Apiumhub

APRIL 8, 2021

With the Data Science industry continually evolving, there can be a lot to keep up with. Adrian specializes in mapping the Database Management System (DBMS), Big Data and NoSQL product landscapes and opportunities. He also manages the LinkedIn group Awesome Ways Big Data Is Used to Improve Our World.

Artificial Inteligence 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

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. Introducing data engineering and data science expertise.

Analytics 102

Analytics Technical Review Technology Applications 102

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. Key takeaways 2.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

MARCH 30, 2023

Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning.

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Weak Development Team Machine Learning Artificial Inteligence Software Review 64