Altexsoft

APRIL 5, 2021

In recent history, the unprocessed and raw information that we call data has gained an increasing amount of traction due to companies realizing its potential. For a layman, this is exactly what started the buzz around big data. Only useable for data-oriented developers or analysts. Data Integration for Marketing.

Company 78

Company Data Technical Review Analysis 78

CTOvision

JANUARY 18, 2015

This popular gathering is designed to enable dialogue about business and technical strategies to leverage today’s big data platforms and applications to your advantage. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 113

Fractional CTO Program Management Programming Big Data 113

CTOvision

FEBRUARY 4, 2015

If you are into technology and government and want to find ways to enhance your ability to serve big missions you need to be at this event, 25 Feb at the Hilton McLean Tysons Corner. Big data and its effect on the transformative power of data analytics are undeniable. Enabling Business Results with Big Data.

Fractional CTO 134

Fractional CTO Technical Review Big Data Analytics 134

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

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. Who needs a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

Capgemini

NOVEMBER 14, 2022

Productivity along the chain can be enhanced with a data catalog, which is a repository of metadata on information sources from across the enterprise, including data sets, business intelligence reports, visualizations, and conversations. It needed to teach people to fish in the data lake. Please try again.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

Xebia

JANUARY 19, 2023

The following quotes date back to those years: Data Engineers set up and operate the organization’s data infrastructure, preparing it for further analysis by data analysts and scientist. – AltexSoft All the data processing is done in Big Data frameworks like MapReduce, Spark and Flink.

Data Engineering 130

Data Engineering Engineering Data Technical Review 130

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Separated Big Data cluster from other programs for Data Science / Discovery to isolate workloads.

Data 84

Data Analytics Cloud Technical Review 84

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

Altexsoft

OCTOBER 29, 2020

Here, we introduce you to ETL testing – checking that the data safely traveled from its source to its destination and guaranteeing its high quality before it enters your Business Intelligence reports. The terms “data warehouse testing” and “ETL testing” are often used interchangeably and that’s not a huge mistake.

Testing 63

Testing Tools Software Review Technical Review 63

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). Under Guadagno, the Deerfield, Ill.-based

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

Altexsoft

MARCH 18, 2021

ETL and ELT are the most widely applied approaches to deliver data from one or many sources to a centralized system for easy access and analysis. 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).

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Sunflower Lab

OCTOBER 2, 2023

Microsoft Azure’s Synapse Analytics is an integrated platform solution that brings together the capability of data warehousing, data connectors, ETL pipelines, analytics tools, and services, as well as the scale for big data, visualization, and dashboards.

Azure 40

Azure Analytics UI/UX Software Review 40

Altexsoft

FEBRUARY 10, 2021

New approaches arise to speed up the transformation of raw data into useful insights. Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. Data analysis. Data visualization/reporting.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

NOVEMBER 9, 2021

If you use a separate RFI (Request for information), RFP (Request for Proposal), or RFQ (Request for Quote) platform, you’ll have to integrate it with your ERP or procurement system to collect the necessary supplier data. Price analysis dashboard by Sievo with opportunities overview. Compliance evaluation. Fraud detection.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Apiumhub

APRIL 27, 2021

Over the last decade, advances in processing power and speed have enabled us to move beyond manual, tedious and time-consuming practices to quick, easy and automated data analysis. The more complex the data sets collected, the more potential there is to uncover relevant insights. What is Data Mining.

Artificial Inteligence 105

Artificial Inteligence Data Machine Learning Artificial Intelligence 105

Mobilunity

NOVEMBER 24, 2021

In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. In this article, we’ll discuss the role of an ETL engineer in data processing and why businesses need such experts nowadays.

Development 52

Development Storage Recruiting Architecture 52

Altexsoft

DECEMBER 17, 2019

In the business sphere, a certain area of technology aims at helping people make the right decisions, by supporting them with the right data. This field is called business intelligence or BI. What is SAP Business Intelligence? Database and data management solutions. SAP Business Intelligence.

Business Intelligence 19

Business Intelligence Weak Development Team Systems Review Software Review 19

Existek

JANUARY 27, 2023

One of the biggest challenges is regulatory compliance. Financial services companies must comply with a wide range of regulations, such as the General Data Protection Regulation (GDPR) and the Payment Services Directive (PSD2), which can make software development more complex and costly.

Software Development 52

Software Development Trends Technology Software 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. Typically used for data analysis and reporting, data warehouses rely on ETL mechanisms to extract , transform , and load data into a destination.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

JANUARY 14, 2021

You may also find it under the name of an enterprise data warehouse (EDW). It is usually created and used primarily for data reporting and analysis purposes. As such, it is possible to retrieve old archived data if needed. Summarized touches upon the fact the data is used for data analytics. Integrations.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

SEPTEMBER 21, 2023

Analysis of logs, metrics, and security events. Business workflow automation. You can leverage Elasticsearch as a storage engine to automate complex business workflows, from inventory management to customer relationship management (CRM). Geospatial analysis. Framework Programming The Good and the Bad of Node.js

Weak Development Team 52

Weak Development Team Analytics Engineering Development Team Review 52

Altexsoft

JUNE 20, 2019

One of the SQL fundamentals is ACID compliance (Atomicity, Consistency, Isolation, Durability). The ACID-compliance is a preferred option if you build, for instance, eCommerce or financial applications, where database integrity is critical. Limited compliance with SQL standards. Cons of MariaDB. Still growing community.

Systems Review 85

Systems Review System Software Review Open Source 85

Cloudera

MAY 16, 2018

The chart below illustrates a scenario in which distinct surveillance teams, each good at what they do, monitor legal entity data, electronic communications, market activity, audio, server logs/sensors, and video.

Analytics 42

Analytics Groups Enterprise Data 42

Altexsoft

OCTOBER 17, 2019

Low-quality data can also impede and slow down the integration of business intelligence and ML-powered predictive analytics. US company executives that participated in the Data trust pulse survey by PricewaterhouseCoopers noted that unreliable data is one of the obstacles to monetizing data.

Tools 16

Tools Data Technical Advisors Technical Review 16

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

Sunflower Lab

APRIL 2, 2024

From unraveling the essence of predictive analytics to the intricacies of turning data points into dollar signs, this comprehensive guide will prime you for a predictive power play that resonates throughout your enterprise. Next, contextualizing these insights within the broader business landscape is crucial.

Analytics 40

Analytics Machine Learning Artificial Inteligence Analysis 40

Altexsoft

FEBRUARY 3, 2020

A study reveals that data-driven organizations are 23 times more likely to acquire customers than their less proactive competitors. This is only one but a very important parameter that proves the power of big data in modern business operations. Data Analytics Definition, Stats, and Benefits. How does it work?

Analytics 87

Analytics Tools Data Artificial Inteligence 87

Altexsoft

MARCH 30, 2023

To dive deeper into details, read our article Data Lakehouse: Concept, Key Features, and Architecture Layers. The lakehouse platform was founded by the creators of Apache Spark , a processing engine for big data workloads. The platform can become a pillar of a modern data stack , especially for large-scale companies.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Altexsoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data use component in a modern data stack.

Data 59

Data Technical Review Software Review Artificial Inteligence 59