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. Ground level of analytics. Gut feeling in decision making.

Analytics 102

Analytics Technical Review Technology Applications 102

DataRobot

SEPTEMBER 6, 2022

Everyone needs to work together to achieve value, from business intelligence experts, data scientists, and process modelers to machine learning engineers, software engineers, business analysts, and end users. You can also go beyond regular accuracy and data drift metrics.

Artificial Inteligence 52

Artificial Inteligence Analytics Data Machine Learning 52

Altexsoft

JANUARY 26, 2022

In addition to understanding data and how it is going to be used, an analytics engineer has to be pretty tech-savvy to apply software engineering best practices to the analytics. The fact that an analytics engineer is officially a thing is out of the question. Defining data quality rules, standards, and metrics.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

Altexsoft

OCTOBER 3, 2019

People analytics is the analysis of employee-related data using tools and metrics. Dashboard with key metrics on recruiting, workforce composition, diversity, wellbeing, business impact, and learning. Choose metrics and KPIs to monitor and predict. How are given metrics interconnected with each other? Commute time.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Abhishek Tiwari

JULY 20, 2019

ERP engineering squad - supply chain planning, purchase order management, product lifecycle management, merchandise planning, etc. Back-office engineering squad - customer support, business intelligence, real-estate management, systems for finance & HR, etc. You want to move fast. How is that even possible?

Engineering 61

Engineering Weak Development Team Software Review Technical Review 61

Honeycomb

NOVEMBER 13, 2018

Metrics and logs. In the past, we mostly monitored and debugged our production system through metrics and logs. On the one hand, we have low-cardinality metrics. This makes it impossible to use metrics to answer questions such as: How many users are affected by this issue? That is great for alerting. Which ones?

Metrics 40

Metrics Engineering Open Source Performance 40

Altexsoft

DECEMBER 14, 2020

Each post contains some metrics like shares or hashtags that can be quantified and structured. What we’re trying to say here is, it will take some time, effort, knowledge, and special software tools to analyze the posts and collect useful insights. The travel agency Facebook post: an example of unstructured data. OLAP applications.

Data 93

Data Artificial Inteligence Storage Analytics 93

Mobilunity

MARCH 26, 2024

SAP NetWeaver Business Warehouse (BW): As a matter of fact this component does not only change raw data into meaningful insights but it also serves as a hub where data from multiple sources can be consolidated thus providing an inclusive business intelligence and reporting platform.

Project Management 52

Project Management Recruiting Agile Quality Assurance 52

Altexsoft

FEBRUARY 11, 2023

machine learning and deep learning models; and business intelligence tools. Setting a data governance policy A data governance policy is a document that covers data management goals, procedures, and business expectations. It defines metrics and best practices to ensure data quality as well as data privacy and security.

Data 87

Data Data Engineering Big Data Architecture 87

Mobilunity

DECEMBER 9, 2024

Education and certifications for AI engineers Higher education base. AI engineers need a strong academic foundation to deeply comprehend the main technology principles and their applications. As supposed, ML engineers need a deep educational background. Business Intelligence developer.

Engineering 52

Engineering Artificial Inteligence Machine Learning Artificial Intelligence 52

Agile Engine

DECEMBER 27, 2023

Establish goals and metrics: Define the key performance indicators (KPIs) or metrics that will measure success in addressing the problem or achieving objectives. Look at their range of services offered
 A comprehensive suite of services suggests a well-rounded understanding of data management, data analytics, and business intelligence.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

DECEMBER 23, 2022

As said, ETL and ELT are two approaches to moving and manipulating data from various sources for business intelligence. In ETL, you first decide what you’re going to do with data, set metrics, and only after that you load and use that data. Postman — a tool that allows software engineers to develop and validate APIs.

Tools 52

Tools Software Review Systems Review Testing 52

Openxcell

JANUARY 3, 2025

Over the years, the company has provided AI, data, mobile, and enterprise software applications in the cloud for some of the leading brands worldwide. They have an excellent team of software engineers, data science professionals, and cloud specialists who continuously resolve problems and complex tasks and enhance projects progressively.

Artificial Inteligence 40

Artificial Inteligence Company Development Artificial Intelligence 40

Altexsoft

JANUARY 25, 2022

Software engineering and consulting companies with experience in the healthcare industry. Applying to companies of this type makes perfect sense if you are not going to replace your current software but only want to enhance some functionality. Development vs purchasing. Out-of-the-box RIS vendors.

System 52

System How To Weak Development Team Healthcare 52

Altexsoft

JULY 19, 2022

It’s often used by internal apps managing business processes — ERPs, accounting software, and medical practice management systems , to name just a few. The analytical plane embraces data that is collected and transformed for analytical purposes such as enterprise reporting, business intelligence , data science , etc.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

JULY 18, 2023

Whether you’re a data scientist, software engineer, or big data enthusiast, get ready to explore the universe of Apache Spark and learn ways to utilize its strengths to the fullest. 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

Bernd Rucker

MAY 27, 2020

Are all engines doing well? And in case you run the enterprise edition, you want to collect metrics from various engines to check that you are in your license limits. We automatically harvested the relevant data from different engines within the company. Professional Developers are trained software engineers.

Programming 52

Programming Company Architecture Technical Review 52

Altexsoft

MARCH 24, 2021

applying business intelligence tools to draw insights from data. With all metrics in hand, healthcare businesses can better understand conditions of their patients, prevent adverse events, develop better diet and treatment plans, and manage chronic diseases more effectively. This include. What can you build with the API?

Tools 69

Tools Healthcare Insurance Video 69