Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Read why the future of data lakehouses is open. Enhanced multi-function analytics.

Cloud 80

Cloud Data Analytics Machine Learning 80

Altexsoft

APRIL 26, 2022

Semi-structured data is somewhere in the middle, meaning it is partially structured but doesn’t fit the tabular models of relational databases. Examples are JSON, XML, and Avro files. The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. cloud services (client) layer.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Cloudera

MAY 13, 2021

For example, a user identified by “3xksle8z” runs only 3% of the queries, yet consumes far more memory than any other user, consuming about 5.9 For example, we see a large number of joins in these queries: Too many joins and inline views characterize inefficiently written SQL. Fixed Reports / Data Engineering jobs .

Data Engineering 73

Data Engineering Cloud Weak Development Team Resources 73

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. Data scientists love Python, period.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

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

TIBCO - Connected Intelligence

APRIL 22, 2021

In its annual Worldwide Global Datasphere Forecast, 2019-2023, IDC projected that only 15% of annual data growth is actually net new data. That means 85% of data growth results from copying data you already have. Opportunity 4: Migrate to the cloud. How data virtualization helps you optimize your queries.

Sustainability 46

Sustainability Virtualization Data Energy 46

Abhishek Tiwari

DECEMBER 22, 2017

Cheap storage and on-demand compute in the cloud coupled with the emergence of new big data frameworks and tools are forcing us to rethink the whole ETL and data warehousing architecture. If the majority of your data is unstructured such as text, images, documents, etc. Classic ETL. Late transformation.

Storage 40

Storage Big Data Google Cloud Analysis 40

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. Phases of the data migration process. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

O'Reilly Media - Ideas

JANUARY 25, 2024

C++ is an ideal language for embedded systems, which often require software that runs directly on the processor (for example, the software that runs in a smart lightbulb or in the braking system of any modern car). Data analysis and databases Data engineering was by far the most heavily used topic in this category; it showed a 3.6%

Trends 116

Trends Technical Review Technology Artificial Inteligence 116

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 topic, in turn, is divided into partitions — the smallest units of storage space, hosting an ordered sequence of messages. For example, LinkedIn employs over 100 clusters with more than 4,000 brokers.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

O'Reilly Media - Ideas

JANUARY 25, 2022

For example, interest in security, after being steady for a few years, has suddenly jumped up, partly due to some spectacular ransomware attacks. To take one example, at this point, the platform has no content on the QUIC protocol or HTTP/3. Both “GCP” and “Google Cloud” were in the top 3% of their respective lists.

Trends 110

Trends Technical Review Technology Artificial Inteligence 110

Perficient

FEBRUARY 16, 2024

In this blog post, we’ll explore into what DBFS is, how it works, and provide examples to illustrate its usage. DBFS is a distributed file system that comes integrated with Databricks, a unified analytics platform designed to simplify big data processing and machine learning tasks. What is DBFS?

System 52

System Storage Azure Big Data 52

Cloudera

DECEMBER 12, 2018

In the Hadoop world, or the big data world, most of these components are separate and modular, but yet interact together to form a system that behaves very similarly. For example, Impala uses the Hive metastore catalog as its data dictionary and it operates directly on data existing in HDFS, which is found through the Namenode API.

Data 42

Data Marketing Storage Big Data 42

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. 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. Stream processing.

Analytics 20

Analytics Data IoT Analysis 20

Confluent

OCTOBER 16, 2019

Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. With tools like KSQL and Kafka Connect, the concept of streaming ETL is made accessible to a much wider audience of developers and data engineers. train_id" : "161Y82MG06".

Data 19

Data Training Analytics Storage 19

Daniel Bryant

SEPTEMBER 13, 2019

What was worth noting was that (anecdotally) even engineers from large organisations were not looking for full workload portability (i.e. There were also two patterns of adoption of HashiCorp tooling I observed from engineers that I chatted to: Infrastructure-driven?—?in Bravo @HashiCorp ??

Infrastructure 8

Infrastructure Azure Software Engineering Cloud 8