Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Business Problem & Background.

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OpenCredo

JULY 31, 2018

Agile and DevOps practices enable the continuous delivery of business value through productionised machine learning models and software delivery. To many of you reading this blog post, the notion that IT is often viewed as a Cost Centre will come as no surprise. Artificial intelligence produces actions. IT as a Cost Centre.

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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?

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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. .

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Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

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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.

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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 ). Read why the future of data lakehouses is open.

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Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ).

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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.

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Cloudera

NOVEMBER 19, 2020

It enables public sector agencies to tap the power of big data and machine learning by managing volume, velocity, and variety of data, bringing unified governance, data integration, and open-source data management capabilities across all cloud and hybrid-cloud environments. Fraudulent Activity Detection.

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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. Data lakes are mostly used by data scientists for machine learning projects.

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Datavail

JUNE 15, 2023

The Microsoft Fabric platform includes: Power BI : The Microsoft business intelligence tool that’s a mainstay for many organizations, infused with a generative AI copilot for business analysts and business users. Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources.

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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.

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Cloudera

JULY 9, 2018

It is cliché to discuss IT/business solutions as people, process, and technology. Some call it the “golden triangle,” but in this blog, we refer to it as the iron triangle. Since the 1960s, technology has disrupted business through the advent of computing and information management. The New Iron Triangle.

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Cloudera

SEPTEMBER 9, 2018

Cloudera Altus offers several key integrated services for data warehousing needs: Altus Data Engineering for building data pipelines and running ETL workflows. Altus Data Warehouse for SQL and business intelligence reporting and analytics. SDX for Altus for shared data context (data catalog).

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Cloudera

NOVEMBER 2, 2020

Data streamed in is queryable immediately, in an optimal manner. Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Data Model. Conventional enterprise data types. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse.

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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.

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TIBCO - Connected Intelligence

DECEMBER 20, 2021

TIBCO Cloud Integration was identified as a “Leader” in four analyst reports, including the 2021 Gartner ® Magic Quadrant for EiPaaS , the Forrester Wave Enterprise iPaaS, Q4, 2021 , the 2021 Nucleus Research iPaaS Value Matrix , and the 2021 Aragon Research Globe Digital Business Business Platform Report.

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Datavail

MARCH 10, 2022

Simply put, data governance is the “ set of processes/policies/strategies that manage the availability, usage/usability, security, and integrity of an organization’s enterprise business data.” ” Data governance is critical in the present and future business landscape.

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Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Many of us are all too familiar with the traditional way enterprises operate when it comes to on-premises data warehousing and data marts: the enterprise data warehouse (EDW) is often the center of the universe.

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Altexsoft

OCTOBER 21, 2022

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker.

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Cloudera

MARCH 2, 2021

However, in the typical enterprise, only a small team has the core skills needed to gain access and create value from streams of data. This data engineering skillset typically consists of Java or Scala programming skills mated with deep DevOps acumen. A rare breed. A rare breed. The difficulty with querying streams.

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Datavail

SEPTEMBER 8, 2022

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. What’s more, 20 percent of these companies are using 1,000 or more sources, far too many to be properly managed by human data engineers.

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