Altexsoft

JUNE 14, 2021

If the user’s data indicate the emergence of a serious medical condition, they can send the customer content designed to change their detrimental lifestyle or recommend immediate treatment. Key insurance personalization strategies. This is possible because their machine learning model is retrained almost daily.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

Altexsoft

FEBRUARY 8, 2021

diversity of sales channels, complex structure resulting in siloed data and lack of visibility. These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

Mobilunity

DECEMBER 28, 2022

Machine Learning is a rapidly-growing field that is revolutionizing the way businesses work and collect data. The process of machine learning involves teaching computers to learn from data without being explicitly programmed. The Services That Machine Learning Engineers Can Offer.

Machine Learning 52

Machine Learning Artificial Inteligence Engineering How To 52

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

Altexsoft

APRIL 13, 2023

The annual IHS Markit Supply Chain Survey Report found that 63 percent of companies don’t have sufficient technology to approach their top priority optimization strategy, i.e., spend analytics (the situation within other strategic areas is similar). to develop all the data architecture and analytics solutions. Data siloes.

Technical Review 59

Technical Review Software Review Analytics 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.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a part of the data governance process which, in turn, is an element of the overall data management strategy. Today, such modern data management frameworks as DataOps strongly rely on effective metadata capture and management to bring order into the chaotic data flows.

Tools 59

Tools Technical Review Software Review Systems Review 59

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

Cloudera

NOVEMBER 19, 2020

In financial services, another highly regulated, data-intensive industry, some 80 percent of industry experts say artificial intelligence is helping to reduce fraud. Machine learning algorithms enable fraud detection systems to distinguish between legitimate and fraudulent behaviors. Fraudulent Activity Detection.

Government 120

Government Artificial Inteligence Machine Learning Data 120

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. Adopting AI can help data quality.

Weak Development Team 126

Weak Development Team Data Technical Review Survey 126

Datavail

JUNE 15, 2023

“It unifies the business model across all the different types of analytics workloads, whether they’re SQL, machine learning – whatever job you want, you can use the same compute infrastructure. Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources.

Azure 52

Azure Analytics Storage Generative AI 52

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 Machine Learning 52

Altexsoft

DECEMBER 23, 2022

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. ELT vs ETL. Please note!

Tools 52

Tools Software Review Systems Review Testing 52

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

ParkMyCloud

MAY 29, 2019

Cloud Architects are experts responsible for the supervision of a company’s cloud computing system, overseeing the organization’s cloud computing strategy through deployment, management, and support of cloud applications. Business Intelligence Analyst. IoT Engineer. Data Detective. Cloud Architect.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

FEBRUARY 22, 2022

However, serious failures can still occur with preventive strategy. Such an approach requires a great deal of investment since a whole ecosystem has to be created, including IoT sensors installation, acquiring specialized software, creating and maintaining machine learning (ML) models, engaging IT and data science specialists , and so on.

Software Review 52

Software Review Technical Review Software Technology 52

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 Machine Learning 52

Altexsoft

NOVEMBER 9, 2021

Traditional statistical methods use mainly internal, historical data to predict trends within relatively stable markets. Meanwhile, machine learning (ML) techniques are capable of processing a wide range of both historical and current data from multiple external and internal sources. Price forecast with Beroe.

Analytics 52

Analytics Software Review Systems Review Technical 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. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

MARCH 18, 2021

From the late 1980s, when data warehouses came into view, and up to the mid-2000s, ETL was the main method used in creating data warehouses to support business intelligence (BI). As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Cloud 52

Cloud Data Firewall AWS 52

Altexsoft

JULY 29, 2022

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. According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Robust community.

Big Data 59

Big Data Data Google Cloud Storage 59

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. Architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

OCTOBER 3, 2019

People analytics is the analysis of employee-related data using tools and metrics. Mark Huselid highlights that the goal of HR analytics activities is to understand, quantify, manage, and improve the role of talent in the execution of strategy and value creation. Let’s explore several popular areas of its application.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Cloudera

NOVEMBER 2, 2020

It is very hard to maintain interactive performance, over large amounts of data that is arriving very fast, some of which might need updates, with a large number of queries of varying patterns. As such, many customers are building RTDW applications as part of their overall strategy of using Cloudera to modernize their data warehouse practice.

Data 97

Data Analytics Storage Big Data 97

Altexsoft

DECEMBER 14, 2022

The heart and soul of Docker are containers — lightweight virtual software packages that combine application source code with all the dependencies such as system libraries (libs) and binary files as well as external packages, frameworks, machine learning models, and more. The Good and the Bad of the SAP Business Intelligence Platform.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

MAY 14, 2021

On top of that, new technologies are constantly being developed to store and process Big Data allowing data engineers to discover more efficient ways to integrate and use that data. You may also want to watch our video about data engineering: A short video explaining how data engineering works.

Big Data 78

Big Data Analytics Tools Applications 78

StubHub

SEPTEMBER 20, 2018

Example of data powering audience optimization (left) and content optimization (right) in CRM. The personalization of data means that every person who engages with the site will be uniquely distinguished from everyone else. One uniform strategy won’t work for all customers?—?as as we know, every customer is unique.

Data 40

Data Scalability Analytics Sport 40

TIBCO - Connected Intelligence

DECEMBER 20, 2021

TIBCO DQ will become the new data quality product family, through an evolution of our current data quality offerings, significantly enhancing current capabilities available throughout the TIBCO data fabric with built-in AI and ML to automate quality, detection, monitoring, and anomaly resolution.

Innovation 26

Innovation Analytics Virtualization Cloud 26

Apiumhub

APRIL 8, 2021

Marcus Borba is a Big Data, analytics, and data science consultant and advisor. Borba has been named a top Big Data and data science influencer and expert several times. He has also been named a top influencer in machine learning, artificial intelligence (AI), business intelligence (BI), and digital transformation.

Artificial Inteligence 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

Altexsoft

NOVEMBER 22, 2019

And no less importantly, they can collect data on their staff, guests, and cleaning patterns, adjusting the workflow if necessary. Room rate data. To set a pricing strategy, you need to have data about room rates of your competitors. Data processing in a nutshell and ETL steps outline. Source: DJUBO.

Hotels 18

Hotels Data Technical Review Systems Review 18

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

CIO

MAY 11, 2023

We leverage artificial intelligence, machine learning, and analytics to offer a hyperpersonalized, immersive, and entertaining gameplay experience to our users at every stage of their gaming journey in real-time. Data is the key for making informed decisions and building customer experiences.

Games 174

Games Artificial Inteligence Data Artificial Intelligence 174

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. They differ from one data consultancy to the next, but here’s what you can generally expect.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. Besides that, it’s fully compatible with various data ingestion and ETL tools. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

TIBCO - Connected Intelligence

SEPTEMBER 29, 2021

“There was a lot of data sprawl, and as a data scientist, it was tough to access all the data from different sources.”. “We Having easier access to data has eliminated the need for basic data engineering, and now our data scientists can do analysis and business intelligence work instead.”.

Data 49

Data Artificial Inteligence Energy Artificial Intelligence 49