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.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

MARCH 31, 2020

It means you must collect transactional data and move it from the database that supports transactions to another system that can handle large volumes of data. And, as is common, to transform it before loading to another storage system. But how do you move data? Data pipeline components. Data pipeline components.

Data 76

Data Storage Analytics Data Center 76

O'Reilly Media - Data

APRIL 3, 2018

Strata Data London will introduce technologies and techniques; showcase use cases; and highlight the importance of ethics, privacy, and security. The growing role of data and machine learning cuts across domains and industries. Data Science and Machine Learning sessions will cover tools, techniques, and case studies.

Machine Learning 159

Machine Learning Artificial Inteligence Company Case Study 159

Altexsoft

NOVEMBER 28, 2019

But, as a business, you might be interested in extracting value of this information instead of just collecting it. Business intelligence (BI) is a set of technologies and practices to transform business information into actionable reports and visualizations. Who is a business intelligence developer?

Business Intelligence 22

Business Intelligence Technical Review Development Storage 22

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

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. Examples are JSON, XML, and Avro files. Each node has its own disk storage.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. Developing business intelligence gives them a distinct advantage in any industry. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies.

Big Data 52

Big Data Data Development Business Intelligence 52

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. 150 for storage use = $15 / TB / month x 10 TB.

Data 98

Data Technical Review Storage Systems Review 98

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Is it still so?

Backup 115

Backup Azure Software Review Systems Review 115

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. More formats, more engines, more interoperability.

Data 94

Data Analytics Open Source Architecture 94

Altexsoft

DECEMBER 9, 2020

Some well-known and widely quoted examples are Albert Einstein saying, “The intuitive mind is a sacred gift,” and Steve Jobs with his “Have the courage to follow your heart and intuition.”. In the era of global digital transformation , the role of data analysis in decision-making increases greatly. Ground level of analytics.

Analytics 102

Analytics Technical Review Technology Applications 102

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. For example, financial numerics of different formats $34.50, 0.90

Development 44

Development Software Engineering Data Engineering Architecture 44

Altexsoft

OCTOBER 2, 2020

Data is a valuable source that needs management. If your business generates tons of data and you’re looking for ways to organize it for storage and further use, you’re at the right place. Read the article to learn what components data management consists of and how to implement a data management strategy in your business.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering. Feature engineering.

Data Engineering 98

Data Engineering Engineering Data Machine Learning 98

ParkMyCloud

MAY 29, 2019

As more and more enterprises drive value from container platforms, infrastructure-as-code solutions, software-defined networking, storage, continuous integration/delivery, and AI, they need people and skills on board with ever more niche expertise and deep technological understanding. Business Intelligence Analyst. IoT Engineer.

Trends 72

Trends Cloud IoT Artificial Inteligence 72

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. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

Testing 63

Testing Tools Software Review Technical Review 63

Altexsoft

SEPTEMBER 9, 2022

Another example is labeling and categorizing objects in any scientific field, be it archeological finds, chemical samples, or living things in biology. Metadata is basically information that describes other data. It helps us understand the origin, structure, nature, and context of data. Metadata examples. date modified.

Tools 59

Tools Technical Review Software Review Systems Review 59

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

Altexsoft

APRIL 13, 2023

Due to extensive usage of connected IoT devices and advanced processing technologies, SCCTs not only gather data and build operational reports but also create predictions, define the impact of various macro- and microeconomic factors on the supply chain, and run “what-if” scenarios to find the best course of action.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

Altexsoft

OCTOBER 24, 2019

Similar to humans companies generate and collect tons of data about the past. And this data can be used to support decision making. While our brain is both the processor and the storage, companies need multiple tools to work with data. And one of the most important ones is a data warehouse. Subject-oriented data.

Architecture 50

Architecture Enterprise Data Technical Review 50

Altexsoft

AUGUST 19, 2022

In our blog, we’ve been talking a lot about the importance of business intelligence (BI), data analytics, and data-driven culture for any company. Users can easily create a wide range of data-intensive, yet intelligible reports and dashboards and share obtained insights. What is Power used for?

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Kentik

MAY 23, 2017

Imagine a big data time-series datastore that unifies traffic flow records (NetFlow, sFlow, IPFIX) with related data such as BGP routing, GeoIP, network performance, and DNS logs, that retains unsummarized data for months, and that has the compute and storage power to answer ad hoc queries across billions of data points in a couple of seconds.

Network 40

Network Open Source Big Data Load Balancer 40

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. Infinite capacity and scalability The data system?—?including

Data 40

Data Scalability Analytics Sport 40

Altexsoft

JUNE 14, 2021

For example, these companies use customer data from wearable and smart devices to monitor the user’s lifestyle. 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.

Insurance 88

Insurance Machine Learning Artificial Inteligence Policies 88

Altexsoft

FEBRUARY 22, 2022

If, for example, your fleet management system doesn’t have that maintenance module, you can implement specialized fleet maintenance software. Some systems offer additional functions such as fuel tracking, trip logs, documentation management (for example, insurance and registration cards), etc. Processing data.

Software Review 52

Software Review Technical Review Software Technology 52

Altexsoft

NOVEMBER 9, 2021

Traditional statistical methods use mainly internal, historical data to predict trends within relatively stable markets. For example, there’s always demand for major raw materials such as wood, coal, wheat, or steel — and the fluctuations are mostly rather moderate. Price forecast with Beroe. ContractExperience platform.

Analytics 52

Analytics Software Review Systems Review Technical Review 52

Altexsoft

JANUARY 22, 2020

Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. A complete guide to business intelligence and analytics. The role of business intelligence developer.

Analytics 20

Analytics Data IoT Analysis 20

Altexsoft

DECEMBER 14, 2022

A container engine acts as an interface between the containers and a host operating system and allocates the required resources. Containers require fewer host resources such as processing power, RAM, and storage space than virtual machines. A Dockerfile example. The Good and the Bad of the SAP Business Intelligence Platform.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Altexsoft

OCTOBER 3, 2019

Descriptive analytics is used to gather and analyze data that represents the current state of things or historical events. For example, managers can define the average employee tenure across departments or in a company as a whole, find out five critical reasons for people leaving, or compare budgets for personal education by years and units.

Analytics 16

Analytics Company Off-The-Shelf How To 16

Cloudera

AUGUST 30, 2022

But while state and local governments seek to improve policies, decision making, and the services constituents rely upon, data silos create accessibility and sharing challenges that hinder public sector agencies from transforming their data into a strategic asset and leveraging it for the common good. .

Architecture 79

Architecture Data Artificial Inteligence Artificial Intelligence 79

Cloudera

JUNE 30, 2022

Today’s general availability announcement covers Iceberg running within key data services in the Cloudera Data Platform (CDP) — including Cloudera Data Warehousing ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Supercharge your data lakehouse, make it open.

Data 88

Data Analytics Machine Learning Artificial Inteligence 88

Altexsoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 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

JULY 19, 2022

Data mesh is a set of principles for designing a modern distributed data architecture that focuses on business domains, not the technology used, and treats data as a product. For example, your organization has an HR platform that produces employee data. Decentralized data ownership by domain.

Architecture 52

Architecture Data Analytics Data Engineering 52

Altexsoft

NOVEMBER 10, 2021

A data lakehouse , as the name suggests, is a new data architecture that merges data warehouse and data lake into a single whole, aiming at addressing each one’s limitations. In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes.

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. 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. What is Hadoop? Apache Hadoop architecture.

Big Data 59

Big Data Data Google Cloud Storage 59

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. For example, CIS guidelines describe detailed configuration settings to secure your AWS account.

Cloud 52

Cloud Data Firewall AWS 52