Trigent

NOVEMBER 3, 2022

Experts unanimously agree data analytics is here to stay, considering 98% of 3PLs and 93% of shippers believe in having data-driven decision-making capabilities to manage supply chain activities. In comparison, 71% of 3PLs think process quality and performance can be significantly improved with the help of big data.

Analytics 52

Analytics Data IoT Trends 52

Coforge

AUGUST 31, 2020

The drastic shift from traditional and orthodox system frameworks and operations can be unarguably attributed to the influx of intelligent technologies such as Artificial Intelligence, Machine Learning, Big Data, Blockchain/DLT led smart contracts, and widespread usage of cloud systems. .

Insurance 40

Insurance Technology Artificial Inteligence Policies 40

Altexsoft

MAY 14, 2021

Big Data enjoys the hype around it and for a reason. But the understanding of the essence of Big Data and ways to analyze it is still blurred. This post will draw a full picture of what Big Data analytics is and how it works. Big Data and its main characteristics. Key Big Data characteristics.

Big Data 78

Big Data Analytics Tools Applications 78

Altexsoft

OCTOBER 29, 2020

But before you dive in, we recommend you reviewing our more beginner-friendly articles on data transformation: Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

Kentik

SEPTEMBER 11, 2015

In this primer we’ll show how to use FDWs to front-end your own datastores, and to allow JOINs with native PG data and data stored in other FDW-accessible systems. We use FDWs this way at Kentik as part of the Kentik Data Engine (KDE) that powers Kentik Detect, the massively scalable big data-based SaaS for network visibility.

Data 40

Data Authentication Data Engineering Scalability 40

Kentik

JULY 19, 2017

Because “package tracking” in a large network is a big data problem, and traditional network management tools weren’t built for that volume of data. As a point of comparison, Fedex and UPS together ship about 20 million packages per day, with an average delivery time of about one day. Act 3: Big Data SaaS to the Rescue.

Big Data 40

Big Data Network Data Systems Review 40

Mobilunity

NOVEMBER 30, 2022

That’s why a lot of enterprises look for an experienced Big Data engineer to add to their team. And the right data analyst freelance can add innovation factor and boost the company’s performance among the competition. Benefits of Hiring a Data Engineer Freelance. Top Sites to Hire a Data Analyst Freelance.

Data 52

Data How To Recruiting Comparison 52

Altexsoft

AUGUST 19, 2022

Power BI offers a range of visualization options that allow you to view your data from every possible side. There are several main categories of visuals according to their purpose: comparison, (e.g., bubble charts, grouped bars), data over time (e.g., bar/line/area charts, treemaps). correlation (e.g., ranking (e.g.,

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

APRIL 16, 2021

An overview of data warehouse types. Optionally, you may study some basic terminology on data engineering or watch our short video on the topic: What is data engineering. What is data pipeline. OLTP vs OLAP: technology comparison. A comparison chart of OLTP and OLAP database features.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Altexsoft

OCTOBER 8, 2021

But more often than not data is scattered across a myriad of disparate platforms, databases, and file systems. What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. How to choose data integration software: key comparison criteria.

Tools 52

Tools Data Software Review Open Source 52

Altexsoft

MARCH 18, 2021

As data keeps growing in volumes and types, the use of ETL becomes quite ineffective, costly, and time-consuming. Basically, ELT inverts the last two stages of the ETL process, meaning that after being extracted from databases data is loaded straight into a central repository where all transformations occur. Data size and type.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. 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. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 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. This doesn’t apply to cloud ETL, though.

Tools 52

Tools Software Review Systems Review Testing 52

Altexsoft

JANUARY 14, 2021

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. What is a data warehouse? How to choose cloud data warehouse software: main criteria. Criteria to consider when choosing cloud data warehouse products.

Backup 115

Backup Azure Software Review Systems Review 115

Cloudera

OCTOBER 14, 2020

Kubernetes default scheduler: A comparison. Natively support Big Data workloads. YuniKorn is designed for Big Data app workloads, and it natively supports to run Spark/Flink/Tensorflow, etc efficiently in K8s. YuniKorn v.s. Application concept. Applications are a 1st class citizen in YuniKorn. Resource fairness.

Policies 113

Policies Resources Systems Review Technical Review 113

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads.

Strategy 95

Strategy Data Technical Review Weak Development Team 95

Altexsoft

FEBRUARY 8, 2021

Machine learning techniques analyze big data from various sources, identify hidden patterns and unobvious relationships between variables, and create complex models that can be retrained to automatically adapt to changing conditions. Comparison between traditional and machine learning approaches to demand forecasting.

Business Intelligence 87

Business Intelligence Analytics Analysis Data 87

ParkMyCloud

MAY 29, 2019

BI Analyst can also be described as BI Developers, BI Managers, and Big Data Engineer or Data Scientist. The main responsibility of IoT engineers is to help businesses keep up with IoT technology trends.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

Altexsoft

APRIL 26, 2022

With Snowflake, multiple data workloads can scale independently from one another, serving well for data warehousing, data lakes , data science, data sharing, and data engineering. BTW, we have an engaging video explaining how data engineering works. Difficult bulk data migration.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

DECEMBER 14, 2022

While you definitely saw the Docker vs Kubernetes comparison, these two systems cannot be compared directly. If you are a programmer, a DevOps , a data engineer , or any other specialist who wants to use Docker in projects, you should have a clear roadmap of how to get started with this technology.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 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. MDM activities include accumulating, cleansing of data, its comparison, consolidation, quality control. Snowflake data management processes.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 24, 2019

And this is what makes a data warehouse different from a Data Lake. Data Lakes are used to store unstructured data for analytical purposes. But unlike warehouses, data lakes are used more by data engineers/scientists to work with big sets of raw data. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Netflix Tech

SEPTEMBER 10, 2019

Instead of relying on engineers to productionize scientific contributions, we’ve made a strategic bet to build an architecture that enables data scientists to easily contribute. The two main challenges with this approach are establishing an easy contribution framework and handling Netflix’s scale of data.

Analysis 86

Analysis Metrics Software Review Testing 86

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

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. CRM platforms). benchmarking study conducted by independent 3rd party ).

Scalability 89

Scalability Technical Review Data Analytics 89

Cloudera

MAY 18, 2021

The intent of this article is to articulate and quantify the value proposition of CDP Public Cloud versus legacy IaaS deployments and illustrate why Cloudera technology is the ideal cloud platform to migrate big data workloads off of IaaS deployments. data streaming, data engineering, data warehousing etc.),

Cloud 83

Cloud Technical Review Storage Backup 83

O'Reilly Media - Ideas

JANUARY 25, 2022

We used data from the first nine months (January through September) of 2021. When doing year-over-year comparisons, we used the first nine months of 2020. Data analysis” and “data engineering” are far down in the list—possibly indicating that, while pundits are making much of the distinction, our platform users aren’t.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109

O'Reilly Media - Ideas

JANUARY 25, 2021

We’re just saying that when you make comparisons, you have to be careful about exactly what you’re comparing. The biggest challenge facing operations teams in the coming year, and the biggest challenge facing data engineers, will be learning how to deploy AI systems effectively. The horse race? That’s just what it is.

Programming 145

Programming Cloud Artificial Inteligence Machine Learning 145