Knowledge Hut

NOVEMBER 2, 2023

The goal is to create a data pipeline that collects and analyses surf data from the Surfline API before storing it in a Postgres data warehouse. Data Aggregation Working with a sample of big data allows you to investigate real-time data processing, big data project design, and data flow.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

JULY 27, 2023

Data quality engineers also need to have experience operating in cloud environments and using many of the modern data stack tools that are utilized in building and maintaining data pipelines. 78% of job postings referenced at least part of their environment was in a modern data warehouse, lake, or lakehouse.

Engineering 52

Engineering Healthcare Scala Data Warehouse 52

Knowledge Hut

JUNE 23, 2023

You should be well-versed in Python and R, which are beneficial in various data-related operations. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. Machine learning will link your work with data scientists, assisting them with statistical analysis and modeling. What is Data Modeling?

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Data Engineering Podcast

NOVEMBER 23, 2020

Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud.

Hadoop 100

Hadoop Data Pipeline BI Data Engineering 100

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 Architect 87

Data Architect Certification Generalist Big Data 87

Databand.ai

DECEMBER 13, 2022

We’d be remiss not to share that Joseph was a recent guest on Databand’s MAD Data Podcast , where he discussed ways to keep data systems from becoming unwieldy and shared tips for data teams to manage their data warehouses and keep data pipelines running reliably. You can also watch the video recording.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

AltexSoft

AUGUST 29, 2023

The term data lake itself is metaphorical, evoking an image of a large body of water fed by multiple streams, each bringing new data to be stored and analyzed. Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JANUARY 30, 2024

This data can be structured, semi-structured, or entirely unstructured, making it a versatile tool for collecting information from various origins. The extracted data is then duplicated or transferred to a designated destination, often a data warehouse optimized for Online Analytical Processing (OLAP).

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

phData: Data Engineering

JULY 12, 2022

Depending on the maturity of the data engineer and the organization, how a data engineer models data is likely to vary. To implement dbt, data analysts may need to skill-up in git and partner with IT for initial setup, but they will find it gives a familiar SQL interface for building out data models.

Data Engineering 52

Data Engineering Data Engineer SQL Data 52

Monte Carlo

AUGUST 25, 2023

Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

MAY 14, 2024

The “legacy” table formats The data landscape has evolved so quickly that table formats pioneered within the last 25 years are already achieving “legacy” status. It was designed to support high-volume data exchange and compatibility across different system versions, which is essential for streaming architectures such as Apache Kafka.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. The Hadoop toy. So the first secret to Hadoop’s success seems clear — it’s cute. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Data Engineering Podcast

JANUARY 21, 2024

A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex.

Data Lake 147

Data Lake High Quality Data NoSQL Data Warehouse 147

Databand.ai

AUGUST 30, 2023

Netflix’s Genie is a platform that provides REST-ful APIs to run a variety of big data jobs like Hadoop, Pig, Hive, and Presto. It’s like an abstraction layer between computation frameworks and the underlying infrastructure, making it easy to manage and control distributed data processing jobs.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Edureka

FEBRUARY 9, 2023

Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. Data ingestion, transformation, and storage are among their responsibilities, as are data governance and security. Data Modeling: Data modeling is the process of creating a conceptual representation of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

JANUARY 24, 2024

Supports numerous data sources It connects to and fetches data from a variety of data sources using Tableau and supports a wide range of data sources, including local files, spreadsheets, relational and non-relational databases, data warehouses, big data, and on-cloud data.

BI 98

BI Business Intelligence Non-relational Database Data Analysis 98

U-Next

MARCH 7, 2023

In order to filter out information from the system, it analyzes data from other users and their interactions with the system. What are some of the most popular tools used in big data? Hadoop Scala Spark Flume Define N-gram. The database is optimized so that data can be retrieved more quickly.

Data Mining 96

Data Mining Scala Government Data Governance 96

Data Engineering Podcast

JUNE 11, 2021

In this episode Lak Lakshmanan enumerates the variety of services that are available for building your various data processing and analytical systems. He shares some of the common patterns for building pipelines to power business intelligence dashboards, machine learning applications, and data warehouses.

Google Cloud 100

Google Cloud Cloud Big Data Ecosystem BI 100

ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

FEBRUARY 8, 2017

The need for speed to use Hadoop for sentiment analysis and machine learning has fuelled the growth of hadoop based data stores like Kudu and adoption of faster databases like MemSQL and Exasol. 2) Big Data is no longer just Hadoop A common misconception is that Big Data and Hadoop are synonymous.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

AltexSoft

OCTOBER 8, 2021

Data integration defines the process of collecting data from a number of disparate source systems and presenting it in a unified form within a centralized location like a data warehouse. So, why is data integration such a big deal? Connections to both data warehouses and data lakes are possible in any case.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

phData: Data Engineering

JANUARY 3, 2022

This means it’s business-critical that companies can derive value from their data to better inform business decisions, protect their enterprise and their customers, and grow their business. This comprehensive guide will cover all of the basics of data engineering including common roles, functions, and responsibilities.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

AltexSoft

JUNE 26, 2023

Apache HBase and Apache Cassandra are well-known columnar technologies belonging to the Hadoop big data ecosystem; graph, intended for graph structures where data points are connected through defined relationships — like in Neo4J, Amazon Neptune, and OrientDB. The difference between data warehouses, lakes, and marts.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

JUNE 14, 2023

5 Data pipeline architecture designs and their evolution The Hadoop era , roughly 2011 to 2017, arguably ushered in big data processing capabilities to mainstream organizations. Data then, and even today for some organizations, was primarily hosted in on-premises databases with non-scalable storage.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Cloudera

DECEMBER 14, 2020

That is why we are outlining four reasons that you should consider for upgrading from Hortonworks DataFlow (HDF), Hortonworks Data Platform (HDP) or Cloudera’s Distribution including Apache Hadoop (CDH) to CDP today. . Gain comprehensive and newer streaming capabilities with CDP.

Process 72

Process Kafka Government Big Data 72

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Airflow — An open-source platform to programmatically author, schedule, and monitor data pipelines.

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120

dbt Developer Hub

APRIL 16, 2023

With these principles in mind, we designed a highly scalable architecture, leveraging AWS-native services to extract and load the data into an S3-based data lake and a Redshift cluster Data Warehouse. All of the data transformation occurs in the warehouse with (you guessed it!)

Cloud 59

Cloud Architecture Data Pipeline SQL 59

ProjectPro

NOVEMBER 30, 2021

In extract-transform-load (ETL), data is obtained from multiple sources, transformed, and stored in a single data warehouse, with access to data analysts , data scientists , and business analysts for data visualization and statistical analysis model building, forecasting, etc.

Process 52

Process Data Pipeline Data Warehouse AWS 52

AltexSoft

NOVEMBER 23, 2021

Before we get into more detail, let’s determine how data virtualization is different from another, more common data integration technique — data consolidation. Data virtualization vs data consolidation. The example of a typical two-tier architecture with a data lake and data warehouses and several ETL processes.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Apache Spark is also quite versatile, and it can run on a standalone cluster mode or Hadoop YARN , EC2, Mesos, Kubernetes, etc. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage.

Big Data 52

Big Data Project Metadata Programming Language 52

phData: Data Engineering

JANUARY 3, 2022

This commonly introduces: Database or Data Warehouse API/EDI Integrations ETL software Business intelligence tooling By leveraging off-the-shelf tooling, your company separates disciplines by technology. Instead of manually working with the data, software, and data products, extract the data to unlock the ability to generate insights.

IT 52

IT AWS Software Engineer Software Engineering 52

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. There are several widely used unstructured data storage solutions such as data lakes (e.g.,

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Cloudera

AUGUST 26, 2020

Informatica’s comprehensive suite of Data Engineering solutions is designed to run natively on Cloudera Data Platform — taking full advantage of the scalable computing platform. This allows our customers to reduce spend on highly specialized hardware and leverage the tools of a modern data warehouse. .

Machine Learning 84

Machine Learning BI Big Data Data Warehouse 84

Databand.ai

DECEMBER 20, 2022

Wannes is skilled in R, Python, data analysis, and data mining and regularly writes and speaks at events. He is also active on LinkedIn, sharing his expertise around data ops, data governance, data strategy, and data mesh.

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59