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

Cloudera

DECEMBER 10, 2020

Some data warehousing solutions such as appliances and engineered systems have attempted to overcome these problems, but with limited success. . Recently, cloud-native data warehouses changed the data warehousing and business intelligence landscape. Which technical capabilities make CDW cost-efficient?

Data 98

Data Technical Review Storage Systems Review 98

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).

Architecture 77

Architecture Data Artificial Inteligence Artificial Intelligence 77

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

Altexsoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two. What data mesh IS.

Architecture 52

Architecture Data Analytics Data Engineering 52

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). Lakehouses redeem the failures of some data lakes. And he’s not alone.

Data 349

Data Artificial Inteligence Technical Advisors Technical Review 349

Altexsoft

SEPTEMBER 9, 2022

Today, such modern data management frameworks as DataOps strongly rely on effective metadata capture and management to bring order into the chaotic data flows. Plus, a data fabric architecture design approach is also based on metadata as one of the main building blocks. Metadata management components.

Tools 59

Tools Technical Review Software Review Systems Review 59

Altexsoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Storage Machine Learning 52

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

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. Transform – moving data in a temporary storage known as a staging area.

Data 76

Data Storage Analytics Data Center 76

Altexsoft

FEBRUARY 10, 2021

Unless you meet it in the article saying that “only 13 percent data science projects make it into production.” This sounds really ominous — especially, for companies heavily investing in data-driven transformations. New approaches arise to speed up the transformation of raw data into useful insights. Data transformation.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

APRIL 26, 2022

Not long ago setting up a data warehouse — a central information repository enabling business intelligence and analytics — meant purchasing expensive, purpose-built hardware appliances and running a local data center. BTW, we have an engaging video explaining how data engineering works.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

JANUARY 14, 2021

We’ll review all the important aspects of their architecture, deployment, and performance so you can make an informed decision. Before jumping into the comparison of available products right away, it will be a good idea to get acquainted with the data warehousing basics first. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

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. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general. How data engineering works in a nutshell.

Weak Development Team 52

Weak Development Team Big Data Data Machine Learning 52

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

MARCH 18, 2021

It is the process of collecting raw data from disparate sources, transmitting it to a staging database for conversion, and loading prepared data into a unified destination system. As the number of disjointed databases grew larger, the need to consolidate all that data into a centralized system grew as well. What is ELT?

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Altexsoft

JULY 29, 2022

According to the study by the Business Application Research Center (BARC), Hadoop found intensive use as. a suitable technology to implement data lake architecture. Apache Hadoop architecture. What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop?

Big Data 59

Big Data Data Google Cloud Storage 59

Mobilunity

DECEMBER 28, 2022

This involves working with clients to identify their ML needs and determine the best approach to meeting those needs. This includes developing algorithms for specific purposes or adapting existing algorithms to meet the needs of a particular application. Modeling is also a critical task for freelancer machine learning engineers.

Machine Learning 52

Machine Learning Artificial Inteligence Engineering How To 52

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. Remember code ownership is overrated.

Engineering 61

Engineering Weak Development Team Software Review Technical Review 61

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. Kafka architecture. Kafka cluster architecture. Kafka cluster and brokers. Scalability.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

OCTOBER 2, 2020

Key disciplines and roles in data management. Data architecture: aligning technologies with business goals. Specialist responsible for the area: data architect. Data architecture is a starting point for any data management model. Snowflake data management processes.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

SEPTEMBER 20, 2019

Not only technological companies are concerned about data analysis, but any kind of business is. Analyzing business information to facilitate data-driven decision making is what we call business intelligence or BI. How is data visualized in BI? Business intelligence data processing in a nutshell.

Business Intelligence 18

Business Intelligence Tools Data Analytics 18

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Friction associated with getting a data sandbox has also resulted in the proliferation of spreadmarts , unmanaged data marts, or other data extracts used for siloed data analysis. Architecture patterns for the cloud.

Cloud 43

Cloud Data Storage Analytics 43

Altexsoft

NOVEMBER 9, 2021

Companies must meet a large number of conditions based on legal regulations to maintain compliance, that include requirements related to. Traditionally, analytics is associated with business intelligence and data visualization that are focused on studying past events and current processes. Extract data.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Cloudera

OCTOBER 25, 2022

“They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”. It allows users to rapidly ingest data and run self-service analytics and machine learning. You can also create metrics to fire alerts when system resources meet specified thresholds.

Cloud 52

Cloud Data Firewall AWS 52

Altexsoft

MAY 14, 2021

It’s represented in terms of batch reporting, near real-time/real-time processing, and data streaming. The best-case scenario is when the speed with which the data is produced meets the speed with which it is processed. Data storage and processing. Hadoop architecture layers. Apache Hadoop. Source: phoenixNAP.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

OCTOBER 3, 2019

Number of days/weeks since a meeting with an HR manager and a department manager. The platform provides “ business intelligence, planning, and predictive capabilities within one product” and uses AI and ML. Data engineer builds interfaces and infrastructure to enable access to data. Compensation.

Analytics 16

Analytics Company Off-The-Shelf How To 16

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. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

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. Predictive analytics, recommendation engines, and AI-driven insights provide businesses with proactive decision support systems, improving accuracy and efficiency.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it.

Data 59

Data Technical Review Software Review Artificial Inteligence 59