Altexsoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. What is the main difference between a data architect and a data engineer? By the way, we have a video dedicated to the data engineering working principles.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JANUARY 6, 2021

Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle. builder.

Artificial Inteligence 134

Artificial Inteligence Machine Learning Data Applications 134

Cloudera

FEBRUARY 9, 2021

In Cloudera Operational Database, you use Apache HBase as a datastore with HDFS and/or S3 providing the storage infrastructure. You have the choice to either develop applications using one of the native Apache HBase applications, or you can use Apache Phoenix for data access. A column family is stored together in the storage. .

Applications 105

Applications Development Storage Database Administration 105

Cloudera

SEPTEMBER 21, 2021

Many customers looking at modernizing their pipeline orchestration have turned to Apache Airflow, a flexible and scalable workflow manager for data engineers. A provider could be used to make HTTP requests, connect to a RDBMS, check file systems (such as S3 object storage), invoke cloud provider services, and much more.

Off-The-Shelf 103

Off-The-Shelf Data Engineering Virtualization Cloud 103

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 Artificial Inteligence 52

Cloudera

FEBRUARY 1, 2024

Moreover, it is a period of dynamic adaptation, where documentation and operational protocols will adapt as your data and technology landscape change. Configuration: set up initial configurations, including cluster settings, user access, and data storage configurations. How does Cloudera support Day 2 operations?

Backup 86

Backup Cloud Architecture Resources 86

Cloudera

JULY 14, 2023

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. All you have to do is to alter the table properties to set the storage handler to “HiveIcebergStorageHandler.”

Backup 73

Backup Data Engineering Engineering Data 73

Erik Bernhardsson

DECEMBER 15, 2020

Note: I'm going to use the term “tool” throughout this post to refer to all kinds of things: frameworks, libraries, development processes, infrastructure.). Decades ago, software engineering was hard because you had to build everything from scratch and solve all these foundational problems.

Software Engineering 304

Software Engineering Engineering Tools Software 304

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.

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

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. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.

Data 86

Data Analytics Cloud Technical Review 86

Altexsoft

SEPTEMBER 9, 2022

Metadata management is a set of activities, technologies, and policies that target metadata collection, storage, and organizing. It aims at making data assets understandable and discoverable for users. Metadata discovery and capture refers to extracting metadata across your data assets. Metadata storage.

Tools 59

Tools Technical Review Software Review Systems Review 59

Cloudera

JANUARY 20, 2021

Now if you want to run and mimic this Demo Application in CDSW, here’s how: Make sure PySpark and HBase are configured – For reference look at Part 1. This application demonstrates how PySpark is leveraged in order to build a simple ML Classification model using HBase as an underlying storage system. Run preprocessing.py

Artificial Inteligence 116

Artificial Inteligence Machine Learning Applications Data 116

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. However, you need to regularly maintain Iceberg tables to keep them in a healthy state so that read queries can perform faster.

Strategy 59

Strategy Travel Groups Data 59

AWS Machine Learning - AI

JANUARY 26, 2024

To simplify implementation of security and privacy best practices, consider using reference designs and infrastructure as code resources such as the AWS Security Reference Architecture (AWS SRA) and the AWS Privacy Reference Architecture (AWS PRA).

Artificial Inteligence 126

Artificial Inteligence Generative AI Security Applications 126

Cloudera

DECEMBER 20, 2022

Today, the costs of sensors, data capture, and information storage have significantly decreased and are one tenth of what they were 10 years ago, leading to the proliferation of data that enables advanced analytics-driving efficiencies. These include recruitment, training, performance management, and employee retention.

Energy 85

Energy Analytics Data Artificial Inteligence 85

Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Abhishek Tiwari

JULY 12, 2018

Unfortunately, building data pipelines remains a daunting, time-consuming, and costly activity. Not everyone is operating at Netflix or Spotify scale data engineering function. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines.

Data 63

Data Software Review Technical Review Microservices 63

Hu's Place - HitachiVantara

NOVEMBER 11, 2018

Hybrid clouds must bond together the two clouds through fundamental technology, which will enable the transfer of data and applications. The term “hyperscale” is used by Gartner to refer to Amazon Web Services, Microsoft Azure, and Google Cloud Platform.

Cloud 78

Cloud Google Cloud Azure AWS 78

Cloudera

SEPTEMBER 17, 2020

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

Data Engineering 105

Data Engineering Engineering Data Tools 105

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

Openxcell

MAY 8, 2023

If you’re still in doubt about how to prevent data leakage, hire a big data engineer. Types of Data Leakage In the World of Data Security, there are many types of data leakage; it is crucial to understand that it can stem from internal or external sources. Cybercriminals do not initiate data leaks.

Data 52

Data Software Review Technical Review Systems Review 52

Altexsoft

AUGUST 19, 2022

Power BI Desktop is a free, downloadable app that’s included in all Office 365 Plans, so all you need to do is sign up, connect to data sources, and start creating your interactive, customizable reports using a drag-and-drop canvas and hundreds of data visuals. You get 10GB of cloud storage and can upload 1GB of data at a time.

Weak Development Team 52

Weak Development Team Data Azure Analytics 52

Altexsoft

MAY 27, 2020

But, in any case, the pipeline would provide data engineers with means of managing data for training, orchestrating models, and managing them on production. Data gathering : Collecting the required data is a beginning of the whole process. Getting additional data from feature store.

Artificial Inteligence 89

Artificial Inteligence Machine Learning Architecture Training 89

Perficient

FEBRUARY 16, 2024

It builds on top of existing file systems like Amazon S3, Azure Blob Storage, and Hadoop HDFS, providing a layer of abstraction and additional functionalities for Spark applications. DBFS provides a unified interface to access data stored in various underlying storage systems. How does DBFS work?

System 52

System Storage Azure Big Data 52

AWS Machine Learning - AI

JUNE 18, 2024

Cost-effective – The solution should only invoke LLM to generate reusable code on an as-needed basis instead of manipulating the data directly to be as cost-effective as possible. Automatic code generation reduces data engineering work from months to days.

Generative AI 104

Generative AI Artificial Inteligence Technical Review AWS 104

Kentik

APRIL 11, 2016

This involves pre-selecting various combinations of dimensions/columns from the source data, and collapsing that data into multiple result sets that contain only those dimensions. Known as “multidimensional online analytical processing” (M-OLAP), this approach is sometimes referred to more succinctly as “data cubes.”

Big Data 40

Big Data Analytics Network Architecture 40

Cloudera

MARCH 23, 2022

Please join us on March 24 for Future of Data meetup where we do a deep dive into Iceberg with CDP . Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer. What is Apache Iceberg? 1: Multi-function analytics .

Data 95

Data Open Source Storage Artificial Inteligence 95

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? The simplest illustration for a data pipeline.

Data 76

Data Storage Analytics Data Center 76

Cloudera

JULY 11, 2023

Impala) and storage (i.e. This also enables advanced scenarios where customers can connect multiple CDW Virtual Clusters to different real-time data mart clusters to connect to a Kudu cluster specific for their workloads. What’s Next For complete setup guide refer to CDW documentation on this topic.

Data 74

Data Virtualization Pharmaceuticals Storage 74

AWS Machine Learning - AI

AUGUST 8, 2024

This solution uses Amazon Bedrock, Amazon Relational Database Service (Amazon RDS), Amazon DynamoDB , and Amazon Simple Storage Service (Amazon S3). The workflow consists of the following steps: An end-user (data analyst) asks a question in natural language about the data that resides within a data lake.

Artificial Inteligence 99

Artificial Inteligence Data Generative AI AWS 99

Mobilunity

NOVEMBER 24, 2021

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. In this article, we’ll discuss the role of an ETL engineer in data processing and why businesses need such experts nowadays. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52

AWS Machine Learning - AI

SEPTEMBER 3, 2024

These runtime roles provide the necessary permissions for your workloads to access AWS resources, such as Amazon Simple Storage Service (Amazon S3) buckets. If you don’t have a SageMaker Studio domain available, refer to Quick setup to Amazon SageMaker to provision one. Install Docker in your JupyterLab environment. python3.11-pip

Serverless 94

Serverless AWS Artificial Inteligence Big Data 94

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 Architecture 115

Perficient

APRIL 1, 2024

Traditionally, organizations used to provision multiple services of Azure Services, like Azure Storage, Azure Databricks, etc. It is crucial that in Premium tab of settings, one needs to choose Fabric capacity (or Trial), which offers Lakehouse (refer below screenshot). Once created, it should look as below (refer below screenshot).

Data 64

Data Azure Case Study Data Engineering 64

Datavail

JUNE 15, 2023

Data Factory : A data integration tool with 150+ connectors to cloud and on-premises data sources. Synapse Data Engineering : A Spark authoring experience that includes instant start with live pools and collaboration features. It triggers notifications and actions when it finds specified patterns in the data.

Azure 52

Azure Analytics Storage Generative AI 52

Netflix Tech

FEBRUARY 9, 2022

Let’s define some requirements that we are interested in delivering to the Netflix data engineers or anyone who would like to schedule a workflow with some external assets in it. This causes the user-managed storage system to be a critical runtime dependency. 39206ee8.3 -> dataflow.egg.hello_world.user.stranger-data.master.39206ee8.2

Data 81

Data Testing Software Review Systems Review 81

Altexsoft

MARCH 16, 2021

In short, this term relates to large amounts of data — both structured and unstructured — that are too voluminous or complex to be processed with traditional software tools. Having described its main characteristics, it becomes clear that not all medical information can be referred to as big data.

Big Data 116

Big Data Healthcare Applications Data 116