O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. An additional 7% are data engineers.

Weak Development Team 145

Weak Development Team Data Technical Review Survey 145

Altexsoft

JANUARY 22, 2020

Such a method requires sending and receiving millions bits of data at any given moment, so that you can play another Black Mirror episode on the go. Similar to a real world stream of water, continuous transition of data received the name streaming , and now it exists in different forms. The role of business intelligence developer.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

DECEMBER 9, 2020

We will describe each level from the following perspectives: differences on the operational level; analytics tools companies use to manage and analyze data; business intelligence applications in real life; challenges to overcome and key changes that lead to transition. Introducing data engineering and data science expertise.

Analytics 102

Analytics Technical Review Technology Applications 102

Altexsoft

OCTOBER 3, 2019

HR specialists can augment background checks with tools that explore and analyze an individual’s activity on social media and other sites and forecast their tendency to express toxic behaviors like sexism, sexual harassment, intolerance, or bullying. Data sources Sickweather uses to predict employee illnesses. Training systems.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Altexsoft

NOVEMBER 22, 2019

Hotel data collection: what and where to look for. A key challenge of hotel data management is the high diversity of available information. It can be extracted from multiple websites, metasearch platforms, social media, internal documents, reports and systems. Important hotel data sets and overlaps between them.

Hotels 18

Hotels Data Technical Review Systems Review 18

Altexsoft

MARCH 31, 2020

These can be data science teams , data analysts, BI engineers, chief product officers , marketers, or any other specialists that rely on data in their work. The simplest illustration for a data pipeline. Data pipeline components. Origin is the point of data entry in a data pipeline.

Data 76

Data Storage Analytics Data Center 76

Exadel

AUGUST 26, 2020

Data Analytics for Better Business Intelligence. Data is king in the modern business world. Thanks to technology, collecting data from just about any aspect of a business is possible — including tracking customers’ activity, desires and frustrations while using a product or service.

Analytics 52

Analytics Data How To Artificial Inteligence 52

Altexsoft

OCTOBER 2, 2020

Data integration and interoperability: consolidating data into a single view. Specialist responsible for the area: data architect, data engineer, ETL developer. Scattered across different storages in various formats, data values don’t talk to each other. Snowflake data management processes.

Strategy 64

Strategy Database Administration Data Technical Review 64

Altexsoft

JUNE 14, 2021

Data obtained from social media activity, fitness trackers, GPS, and other tech can help you serve customers better. You can start investing in data infrastructure and analytical pipelines to automate data collection and analysis mechanisms. You’ll need a data engineering team for that.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

Altexsoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc.

Big Data 78

Big Data Analytics Tools Applications 78

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 Artificial Inteligence 52

Openxcell

JANUARY 3, 2025

Openxcell is always ready to understand your project needs and use AI’s full potential to deliver a solution that propels your business forward. The company offers a wide range of AI Development services, such as Generative AI services, Custom LLM development , AI App Development , Data Engineering , GPT Integration , and more.

Artificial Inteligence 40

Artificial Inteligence Company Development Artificial Intelligence 40

Strategy Driven

FEBRUARY 4, 2021

A good sales intelligence software must be able to merge with other sales software, business intelligence, and analytics or data management solutions. Adapt gives users access to business contacts to build competent leads and interact with new customers faster. LinkedIn Sales Navigator.

Software 34

Software B2B Analytics Business Intelligence 34

Agile Engine

DECEMBER 27, 2023

A data analytics consultancy has a team of specialists and engineers who perform data analytics for companies that don’t have the capacity to do it in-house. It also helps with demand forecasting, route optimization, and understanding customer sentiment through social media analytics.

Big Data 52

Big Data Analytics Data Analysis 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 Artificial Inteligence 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

APRIL 13, 2023

as well as third-party data providers (e.g., market data, weather, maps, social media, etc.). A central data hub To integrate all the information, you need a centralized repository that stores both structured and unstructured data. to develop all the data architecture and analytics solutions. Data siloes.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. This means that companies don’t necessarily need a large data engineering team. Data democratization.

Data 59

Data Technical Review Software Review Open Source 59

Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. In other words, Kafka can serve as a messaging system, commit log, data integration tool, and stream processing platform. 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

JULY 18, 2023

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

Strategy Driven

AUGUST 27, 2015

Big Data involves not just the structured data (customer name and details, products purchased, how much was spent and when, etc.) that every company is used to capturing, but also unstructured data (data scraped from the Internet and social media channels that may come in a wide variety of formats, from video to voice).

Big Data 33

Big Data Data Storage Journal 33

Openxcell

DECEMBER 27, 2024

In addition to AI consulting, the company has expertise in delivering a wide range of AI development services , such as Generative AI services, Custom LLM development , AI App Development, Data Engineering, RAG As A Service , GPT Integration, and more. Deeper Insights has delivered various solutions for businesses worldwide.

Artificial Inteligence 40

Artificial Inteligence Company Generative AI Machine Learning 40

Altexsoft

NOVEMBER 9, 2021

Using internal (such as late delivery or defect rate) and external data (such as supplier company reports, news, aforementioned analytical platforms, or even social media), such solutions can identify risks in advance and help avoid supply chain disruptions by suggesting to substitute the supplier or take preventive measures.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

SEPTEMBER 9, 2022

Metadata capture or extraction is harvesting metadata across your asset landscape, including internal and external data sources like business applications, databases, data warehouses , data lakes , BI tools , webpages, etc. An example of social media post metadata. Source: Pagefreezer. Metadata creation.

Tools 59

Tools Technical Review Software Review Systems Review 59

O'Reilly Media - Ideas

JANUARY 14, 2025

The data in each graph is based on OReillys units viewed metric, which measures the actual use of each item on the platform. It accounts for different usage behavior for different media: text, courses, and quizzes. In each graph, the data is scaled so that the item with the greatest units viewed is 1.

Trends 131

Trends Technology Security Artificial Inteligence 131

CIO

AUGUST 5, 2022

They provide designers with the tools they need to create visual representations of large data sets. Some of the most popular include the following: Domo: Domo is a cloud software company that specializes in business intelligence tools and data visualization. It’s very similar to Excel so Excel skills transfer well.

Data 214

Data Analytics Travel Business Intelligence 214

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 9

Conference Data Data Engineering Big Data 9

CIO

APRIL 4, 2023

I get it, we live in an age of instant gratification, with Doordash and Grubhub meals on-demand, fast-paced social media and same-day Amazon Prime deliveries. Layered on top of that are the different types of data stored in various siloes and locations throughout an organization. In the words of J.R.R.

Architecture 78

Architecture Data Analysis Construction 78