Pickl AI

AUGUST 1, 2023

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

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Data Engineering Data Engineering Data Engineering Data Engineer 52

ODSC - Open Data Science

JANUARY 18, 2024

Data engineering is a rapidly growing field, and there is a high demand for skilled data engineers. If you are a data scientist, you may be wondering if you can transition into data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

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Smart Data Collective

FEBRUARY 23, 2022

The size and the variety of data that enterprises have to deal with have become more complex and larger. Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. In traditional relational database engines, users can plan indexing to improve performance.

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Data Lakes AWS SQL Database 99

The MLOps Blog

JANUARY 23, 2023

However, there are some key differences that we need to consider: Size and complexity of the data In machine learning, we are often working with much larger data. Basically, every machine learning project needs data. First of all, machine learning engineers and data scientists often use data from different data vendors.

ML 52

ML ML Data Lakes Machine Learning 52

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 52

IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

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Data Warehouse Data Engineering Data Engineer Data Engineering 57

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

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Data Engineering Data Engineering Data Engineering Data Engineer 91

ODSC - Open Data Science

JANUARY 30, 2024

Data engineering is a hot topic in the AI industry right now. And as data’s complexity and volume grow, its importance across industries will only become more noticeable. But what exactly do data engineers do? So let’s do a quick overview of the job of data engineer, and maybe you might find a new interest.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform.

AI 52

AI AI Data Science Machine Learning 52

ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

Analytics Analytics Data Analyst SQL 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 85

Data Science Analytics Analytics Data Scientist 85

ODSC - Open Data Science

FEBRUARY 15, 2024

We couldn’t be more excited to announce the first sessions for our second annual Data Engineering Summit , co-located with ODSC East this April. Join us for 2 days of talks and panels from leading experts and data engineering pioneers. Is Gen AI A Data Engineering or Software Engineering Problem?

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Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

FEBRUARY 15, 2024

The Future of the Single Source of Truth is an Open Data Lake Organizations that strive for high-performance data systems are increasingly turning towards the ELT (Extract, Load, Transform) model using an open data lake. To DIY you need to: host an API, build a UI, and run or rent a database.

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Data Lakes AI AI Data Visualization 52

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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Data Warehouse Azure AWS Database 59

Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Snowflake Database Pros Extensive Storage Opportunities Snowflake provides affordability, scalability, and a user-friendly interface.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

IBM Journey to AI blog

MARCH 14, 2024

The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage. Also, traditional database management tasks, including backups, upgrades and routine maintenance drain valuable time and resources, hindering innovation.

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IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. After all, Alex may not be aware of all the data available to her.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

AWS Machine Learning Blog

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

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AI AI ML ML 106

Mlearning.ai

JULY 8, 2023

As it has previously been pointed out, ETL stands for extract, transform and load, and refers to the process that extracts data from a source point, transforms the data in some way and loads the output data to a target point. There are mainly 2 different types of ETL: batch and streaming.

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ETL Azure Python Internet of Things 52

Alation

MARCH 22, 2022

Accenture calls it the Intelligent Data Foundation (IDF), and it’s used by dozens of enterprises with very complex data landscapes and analytic requirements. Simply put, IDF standardizes data engineering processes. They can better understand data transformations, checks, and normalization.

DataOps 52

DataOps Data Pipeline Data Engineering Data Engineer 52

ODSC - Open Data Science

OCTOBER 15, 2023

Cloudera Cloudera is a cloud-based platform that provides businesses with the tools they need to manage and analyze data. They offer a variety of services, including data warehousing, data lakes, and machine learning. ArangoDB ArangoDB is a company that provides a database platform for graph and document data.

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52

IBM Journey to AI blog

OCTOBER 16, 2023

This type of next-generation data store combines a data lake’s flexibility with a data warehouse’s performance and lets you scale AI workloads no matter where they reside. It allows for automation and integrations with existing databases and provides tools that permit a simplified setup and user experience.

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Analytics Vidhya

MARCH 21, 2023

Introduction In today’s world, data is growing exponentially with time with digitalization. to store and analyze this data to get valuable business insights from it. Organizations are using various cloud platforms like Azure, GCP, etc.,

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Alation

NOVEMBER 28, 2022

But refreshing this analysis with the latest data was impossible… unless you were proficient in SQL or Python. We wanted to make it easy for anyone to pull data and self service without the technical know-how of the underlying database or data lake. Sathish and I met in 2004 when we were working for Oracle.

Database 52

Database Data Governance Data Quality Data Lakes 52

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

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AWS Machine Learning Blog

JANUARY 26, 2024

Also consider using Amazon Security Lake to automatically centralize security data from AWS environments, SaaS providers, on premises, and cloud sources into a purpose-built data lake stored in your account.

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AWS Machine Learning Blog

JUNE 5, 2023

Many teams are turning to Athena to enable interactive querying and analyze their data in the respective data stores without creating multiple data copies. Athena allows applications to use standard SQL to query massive amounts of data on an S3 data lake. Create a data lake with Lake Formation.

Machine Learning 73

Machine Learning Machine Learning AWS Data Lakes 73

Flipboard

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. Set up the database access and network access.

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K-nearest Neighbors AWS Clustering Database 126

ODSC - Open Data Science

MAY 16, 2023

Comprehensive data privacy laws in at least four states are going into effect this year, and more than a dozen states have similar legislation in the works. Database management may become increasingly complex as organizations must account for more of these laws.

Database 98

Database Data Lakes Data Science Data Observability 98

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Defining OLAP today OLAP database systems have significantly evolved since their inception in the early 1990s.

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Data Preparation Database AI AI 64

AWS Machine Learning Blog

DECEMBER 18, 2023

In this post, we will explore the potential of using MongoDB’s time series data and SageMaker Canvas as a comprehensive solution. MongoDB Atlas MongoDB Atlas is a fully managed developer data platform that simplifies the deployment and scaling of MongoDB databases in the cloud. Setup the Database access and Network access.

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Clustering AWS Database ML 107

phData

APRIL 2, 2024

By leveraging cloud-based data platforms such as Snowflake Data Cloud , these commercial banks can aggregate and curate their data to understand individual customer preferences and offer relevant and personalized products.

ML 52

ML ML Data Silos Data Lakes 52

phData

SEPTEMBER 20, 2023

A data mesh is a conceptual architectural approach for managing data in large organizations. Traditional data management approaches often involve centralizing data in a data warehouse or data lake, leading to challenges like data silos, data ownership issues, and data access and processing bottlenecks.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lakes 59

Data Lakes Data Governance Data Quality Data Warehouse 59

phData

FEBRUARY 24, 2023

Organizations can unite their siloed data and securely share governed data while executing diverse analytic workloads. Snowflake’s engine provides a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing.

Analytics 52

Analytics Analytics Database Python 52

Flipboard

NOVEMBER 24, 2023

JuMa is tightly integrated with a range of BMW Central IT services, including identity and access management, roles and rights management, BMW Cloud Data Hub (BMW’s data lake on AWS) and on-premises databases. He has a record of working with distributed teams across the globe within large enterprises.

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