CIO

FEBRUARY 13, 2023

Fifty-two percent of organizations plan to increase or maintain their IT spending this year, according to Enterprise Strategy Group. This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%).

Budget 363

Budget Artificial Inteligence Technical Review VR 363

Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

OCTOBER 4, 2023

Fast moving data and real time analysis present us with some amazing opportunities. Every organization has some data that happens in real time, whether it is understanding what our users are doing on our websites or watching our systems and equipment as they perform mission critical tasks for us. Don’t blink — or you’ll miss it!

Analytics 90

Analytics Machine Learning Artificial Inteligence Telecommunications 90

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.

Architecture 52

Architecture Data Storage Machine Learning 52

TIBCO - Connected Intelligence

SEPTEMBER 22, 2020

For today’s most mature enterprise cloud architectures, ultra-quick querying capabilities on petabytes of data is what the modern pace of business demands. And for enterprises running AWS, Amazon Redshift is most certainly a part of the data warehousing picture given its size, flexibility, and scale.

AWS 48

AWS Analytics Cloud Analysis 48

TechCrunch

MARCH 22, 2021

Berlin-based y42 (formerly known as Datos Intelligence), a data warehouse-centric business intelligence service that promises to give businesses access to an enterprise-level data stack that’s as simple to use as a spreadsheet, today announced that it has raised a $2.9

Business Intelligence 244

Business Intelligence Software Review B2B Analytics 244

Capgemini

NOVEMBER 14, 2022

Data has to be easy to find, understand, access, and use for everyone in the chain: data engineers, analysts, data scientists, and business users. It makes the data more accessible and understandable to everyone, especially less-skilled data consumers. The next wave of catalog and self service.

Agile 52

Agile Technical Review Systems Review Artificial Intelligence 52

O'Reilly Media - Ideas

FEBRUARY 11, 2019

The resource examples I’ll cite will be drawn from the upcoming Strata Data conference in San Francisco , where leading companies and speakers will share their learnings on the topics covered in this post. AI and machine learning in the enterprise. AI and machine learning in the enterprise. Foundational data technologies.

Big Data 87

Big Data Technology Tools Cloud 87

Lacework

NOVEMBER 1, 2023

When architecting data systems, a key philosophy is keeping customer privacy front and center both in the design choices made and and options presented to the user, while ensuring the ability to meet business needs and service criteria. What is privacy? A mart is a group of aggregated tables (e.g.,

System Design 52

System Design Systems Review System Data 52

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. . Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics.

Data 85

Data Analytics Cloud Technical Review 85

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

Then, metadata can be analyzed to define how well data is structured, if there are any missing or invalid elements, or how it is related to other data. For example, such an analysis may discover that not all mandatory fields contain data or that certain records are of the incorrect format. Let’s explore what they are.

Tools 59

Tools Technical Review Software Review Systems Review 59

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

Altexsoft

APRIL 13, 2023

To store all this diverse information, you’ll have to utilize a centralized data repository such as a data warehouse or data lake. You can also consider a cloud data lakehouse as an option since it addresses the limitations of the aforementioned repository types and works with various data workloads.

Technical Review 59

Technical Review Software Review Analytics Systems Review 59

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. Watch this video to get an overview of CDW. .

Data 98

Data Technical Review Storage Systems Review 98

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

CIO

AUGUST 18, 2022

Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. The result is an emerging paradigm shift in how enterprises surface insights, one that sees them leaning on a new category of technology architected to help organizations maximize the value of their data.

Data 350

Data Artificial Inteligence Technical Advisors Technical Review 350

CIO

APRIL 4, 2023

Despite these AI-powered examples, businesses have only just begun to embrace AI, with an estimated 12% fully using AI technology. In one Forrester study and financial analysis, it was found that AI-enabled organizations can gain an ROI of 183% over three years. Constructing the right data architecture cannot be bypassed.

Architecture 130

Architecture Data Analysis Construction 130

O'Reilly Media - Ideas

FEBRUARY 11, 2020

Key survey results: The C-suite is engaged with data quality. Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. Adopting AI can help data quality.

Weak Development Team 129

Weak Development Team Data Technical Review Survey 129

Cloudera

FEBRUARY 8, 2021

Having completed the Data Collection step in the previous blog, ECC’s next step in the data lifecycle is Data Enrichment. ECC will enrich the data collected and will make it available to be used in analysis and model creation later in the data lifecycle. 1 The enterprise data lifecycle.

Data 119

Data Technical Review Data Engineering Analysis 119

Altexsoft

APRIL 16, 2021

Namely, we’ll explain what functions it can perform, and how to use it for data analysis. As the topic is closely related to business intelligence (BI) and data warehousing (DW), we suggest you to get familiar with general terms first: A guide to business intelligence. What is data pipeline.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

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

JANUARY 26, 2022

In recent years, it’s getting more common to see organizations looking for a mysterious analytics engineer. As you may guess from the name, this role sits somewhere in the middle of a data analyst and data engineer, but it’s really neither one nor the other. Here’s the video explaining how data engineers work.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Altexsoft

OCTOBER 24, 2019

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. In this article, we will discuss what an enterprise data warehouse is, its types and functions, and how it’s used in data processing.

Architecture 50

Architecture Enterprise Data Technical Review 50

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 2, 2020

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. Fitting into wider enterprise architecture, it outlines how data is collected, integrated, transformed, stored, and used.

Database Administration 64

Database Administration Strategy Data Technical Review 64

Altexsoft

AUGUST 4, 2021

Instead of combing through the vast amounts of all organizational data stored in a data warehouse, you can use a data mart — a repository that makes specific pieces of data available quickly to any given business unit. What is a data mart? Key differences between data marts, data warehouses, and data lakes.

Data 64

Data Analytics Construction Cloud 64

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. While all three are about data acquisition, they have distinct differences.

Artificial Inteligence 52

Artificial Inteligence Machine Learning Data Systems Review 52

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. The primary difference resides in WHERE and WHEN data transformation and loading happens. These are data engineers who are responsible for implementing these processes.

Systems Review 109

Systems Review Technical Review Software Review Compliance 109

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

Exadel

AUGUST 26, 2020

Data Analytics for Better Business Intelligence. Data is king in the modern business world. Thanks to technology, collecting data from just about any aspect of a business is possible — including tracking customers’ activity, desires and frustrations while using a product or service.

Analytics 52

Analytics Data How To Machine Learning 52

Altexsoft

JANUARY 14, 2021

A data warehouse is often abbreviated as DW or DWH. 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. Data warehouse architecture.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

JULY 19, 2022

Through all these shifts, data mesh is called to solve the problems of centralized data platforms by giving more flexibility and independence, agility and scalability, cost-effectiveness, and cross-functionality. Data mesh principles and architecture. And it’s their job to guarantee data quality. It works like this.

Architecture 52

Architecture Data Analytics Data Engineering 52

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Cloud 52

Cloud Data Firewall AWS 52

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. The main idea of any data warehouse (DW) is to integrate data from multiple disjointed sources (e.g.,

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59