Towards Data Science

FEBRUARY 6, 2024

As you do not want to start your development with uncertainty, you decide to go for the operational raw data directly. Accessing Operational Data I used to connect to views in transactional databases or APIs offered by operational systems to request the raw data. Does it sound familiar?

Systems 82

Systems Raw Data Data Cleanse Metadata 82

Ascend.io

AUGUST 31, 2023

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python. Use VDK to build a data lake and merge multiple sources.

Data Lake 86

Data Lake Data SQL Data Warehouse 86

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

ProjectPro

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Ascend.io

JANUARY 2, 2024

The key differentiation lies in the transformational steps that a data pipeline includes to make data business-ready. Ultimately, the core function of a pipeline is to take raw data and turn it into valuable, accessible insights that drive business growth. best suit our processed data? cleaning, formatting)?

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

WeCloudData

OCTOBER 19, 2021

Resolution In order to meet the business requirements for a job market analysis platform & dashboard, WeCloudData helped the client leverage a suite of cloud platforms & tools to enable a data pipeline in multiple stages: Ingest job data from multiple sources and store the raw data in a cloud data lake Process the raw data with Python & (..)

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Resolution In order to meet the business requirements for a job market analysis platform & dashboard, WeCloudData helped the client leverage a suite of cloud platforms & tools to enable a data pipeline in multiple stages: Ingest job data from multiple sources and store the raw data in a cloud data lake Process the raw data with Python & (..)

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. Each of the mastered data sets could be a domain.

Pharmaceutical 98

Pharmaceutical Data Lake Data Warehouse Raw Data 98

Data Engineering Podcast

DECEMBER 11, 2021

In the same way that application performance monitoring ensures reliable software and keeps application downtime at bay, Monte Carlo solves the costly problem of broken data pipelines. Start trusting your data with Monte Carlo today! constraints on data manipulation, security, privacy concerns, etc.)

Data Warehouse 100

Data Warehouse Raw Data Data Lake BI 100

Ascend.io

NOVEMBER 21, 2023

More importantly, we will contextualize ELT in the current scenario, where data is perpetually in motion, and the boundaries of innovation are constantly being redrawn. Extract The initial stage of the ELT process is the extraction of data from various source systems. What Is ELT? So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

DataKitchen

AUGUST 9, 2021

The data industry has a wide variety of approaches and philosophies for managing data: Inman data factory, Kimball methodology, s tar schema , or the data vault pattern, which can be a great way to store and organize raw data, and more. Data mesh does not replace or require any of these.

Pharmaceutical 98

Pharmaceutical Raw Data Data Lake Data 98

Hepta Analytics

FEBRUARY 14, 2022

This week, we got to think about our data ingestion design. We looked at the following: How do we ingest – ETL vs ELT Where do we store the data – Data lake vs data warehouse Which tool to we use to ingest – cronjob vs workflow engine NOTE : This weeks task requires good internet speed and good compute.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Data Engineering Podcast listeners can sign up for a free 2-week sandbox account, go to dataengineeringpodcast.com/tonic today to give it a try!

Data Management 100

Data Management Management MongoDB Scala 100

Data Engineering Podcast

JANUARY 14, 2017

Summary Do you wish that you could track the changes in your data the same way that you track the changes in your code? Pachyderm is a platform for building a data lake with a versioned file system. Interview with Daniel Whitenack Introduction How did you get started in the data engineering space?

Data Lake 100

Data Lake Raw Data Kafka Data Pipeline 100

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake.

Data Lake 79

Data Lake Analytics Application Cloud Storage Architecture 79

Knowledge Hut

OCTOBER 4, 2023

While the numbers are impressive (and a little intimidating), what would we do with the raw data without context? The tool will sort and aggregate these raw data and transport them into actionable, intelligent insights. If this trend continues to evolve, it will nearly double by 2025.

BI 52

BI Systems Raw Data Business Intelligence 52

Knowledge Hut

SEPTEMBER 27, 2023

Big Data support The SPICE engine in QuickSight was built to handle huge datasets, making it suited for big data scenarios. Its capacity to handle large amounts of data increases its flexibility in business settings. This will help your business to take corrective actions in a timely manner.

BI 52

BI AWS Database-centric Data Lake 52

Knowledge Hut

DECEMBER 28, 2023

The Azure Data Engineer certification imparts to them a deep understanding of data processing, storage and architecture. By leveraging their proficiency, they enable organizations to transform raw data into valuable insights that drive business decisions. These equip us with the necessary skills and knowledge to excel.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

FEBRUARY 16, 2023

ETL Architecture on AWS: Examining the Scalable Architecture for Data Transformation ETL Architecture on AWS typically consists of three components - Source Data Store A Data Transformation Layer Target Data Store Source Data Store The source data store is where raw data is stored before being transformed and loaded into the target data store.

AWS 52

AWS Data Management ETL Tools Management 52

Monte Carlo

AUGUST 31, 2023

Data pipelines can handle both batch and streaming data, and at a high-level, the methods for measuring data quality for either type of asset are much the same. In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Databand.ai

AUGUST 30, 2023

Data Storage Once data is ingested, it must be stored in a suitable data storage platform that can accommodate the volume, variety, and velocity of the data being processed. Data storage platforms can include traditional relational databases, NoSQL databases, data lakes, or cloud-based storage services.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

SQL 52

SQL Kafka MongoDB MySQL 52

Grouparoo

OCTOBER 26, 2021

Origin The origin of a data pipeline refers to the point of entry of data into the pipeline. This includes the different possible sources of data such as application APIs, social media, relational databases, IoT device sensors, and data lakes.

Data Pipeline 52

Data Pipeline ETL Tools ETL System Data Warehouse 52

Rockset

JANUARY 31, 2023

SkyHive platform Challenges with MongoDB for Analytical Queries 16 TB of raw text data from our web crawlers and other data feeds is dumped daily into our S3 data lake. That data was processed and then loaded into our analytics and serving database, MongoDB.

MongoDB 59

MongoDB Pharmaceutical Recruitment Raw Data 59

Knowledge Hut

DECEMBER 22, 2023

Power BI is a technology-driven business intelligence tool or an array of software services, apps, and connectors to convert unrelated and raw data into visually immersive, coherent, actionable, and interactive insights and information. Microsoft developed it and combines business analytics, data visualization, and best practices.

BI 98

BI Business Intelligence Machine Learning Data Cleanse 98

Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Rockset

AUGUST 25, 2021

They are an essential part of the modern data stack for powering: Real-time search applications Social features in the product Recommendation/rewards features in the product Real-time dashboards IoT applications These use cases can have several TBs per day streaming in - they are literally data torrents.

Aggregated Data 52

Aggregated Data Data Lake Hadoop SQL 52

Knowledge Hut

JANUARY 19, 2024

Business Intelligence Transforming raw data into actionable insights for informed business decisions. Coding Coding is the wizardry behind turning data into insights. A data scientist course syllabus introduces languages like Python, R, and SQL – the magic wands for data manipulation.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Edureka

JANUARY 23, 2023

Once experts identify the problem, they start collecting relevant data from various sources. These are pooled in a central data lake or warehouse and prepared for analysis. Companies use various data mining functionalities to arrive at the solution they desire. You can learn more about this programme on our website.

Data Mining 52

Data Mining Banking Retail Medical 52

Ascend.io

SEPTEMBER 14, 2023

Python for Data Engineering Use Cases Data engineering, at its core, is about preparing “big data” for analytical processing. It’s an umbrella that covers everything from gathering raw data to processing and storing it efficiently.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Ascend.io

JANUARY 3, 2023

However, most data leaders are finding that technology alone does not cause the organization to deliver new and valuable insights fast enough. Fundamentally, we need an approach that holistically supports the infrastructure, technology, and processes to convert raw data into something valuable and accessible.

Data 52

Data Data Lake Business Intelligence Big Data 52

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake? What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52