Towards Data Science

DECEMBER 1, 2023

Storage —  Snowflake Snowflake, a cloud-based data warehouse tailored for analytical needs, will serve as our data storage solution. The data volume we will deal with is small, so we will not try to overkill with data partitioning, time travel, Snowpark, and other Snowflake advanced capabilities.

Data Engineering 72

Data Engineering Data Engineer Project Engineering 72

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

DECEMBER 21, 2023

Cloud-based storage and analytical platform helps business to easily access their data whenever required irrespective of where it is located physically. Reliability : Cloud providers ensure high reliability to their customers based on their SLA which is useful for the data-driven business to operate 24X7.

Cloud Computing 52

Cloud Computing Cloud Algorithm Healthcare 52

Ascend.io

MAY 23, 2023

The data engineering world is full of tips and tricks on how to handle specific patterns that recur with every data pipeline. Even the data stewards who have taken on responsibility for the accuracy and business relevance of the data are often unaware of the nuances of orphaned datasets. How can you up your game?

Datasets 52

Datasets Data Pipeline Metadata Database 52

Towards Data Science

JANUARY 17, 2024

Parquet vs ORC vs Avro vs Delta Lake Photo by Viktor Talashuk on Unsplash The big data world is full of various storage systems, heavily influenced by different file formats. These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction.

Big Data 72

Big Data Data Data Storage SQL 72

Monte Carlo

JUNE 28, 2022

Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem. By design, data was less structured with limited metadata and no ACID properties. Unity Catalog The Unity Catalog unifies metastores, catalogs, and metadata within Databricks.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

NOVEMBER 28, 2023

Hence, learning and developing the required data engineer skills set will ensure a better future and can even land you better salaries in good companies anywhere in the world. After all, data engineer skills are required to collect data, transform it appropriately, and make it accessible to data scientists.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

JULY 20, 2023

All of them use image encryption to hide them from unauthorized access. The encryption process ensures that even if an attacker gains access to the encrypted image, they cannot retrieve the original content without the decryption key. AES is widely used in secure communication protocols, data storage, and many other applications.

Medical 40

Medical Algorithm Metadata Cloud Storage 40

Snowflake

JULY 10, 2023

With this new Snowpark capability, data engineers and data scientists can process any type of file directly in Snowflake, regardless if files are stored in Snowflake-managed storage or externally. The analyst has read access to the DICOM image files and can create a scoped URL for files using build_scoped_file_url.

Unstructured Data 40

Unstructured Data Python Process Scala 40

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 Warehouse 80

Data Warehouse Database-centric Metadata Cloud 80

Snowflake

APRIL 5, 2023

Traditionally, the dimensional data modeling approach is used to build complex data warehouses, while Data Vaults are used in data warehouses to offer long-term historical data storage while modeling. Why is data modeling important for a data warehouse?

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

Cloudera

OCTOBER 15, 2021

With FSO, Apache Ozone guarantees atomic directory operations, and renaming or deleting a directory is a simple metadata operation even if the directory has a large set of sub-paths (directories/files) within it. In fact, this gives Apache Ozone a significant performance advantage over other object stores in the data analytics ecosystem.

Cloud 86

Cloud Hadoop Data Analytics Metadata 86

RandomTrees

SEPTEMBER 6, 2020

The architecture is three layered: Database Storage: Snowflake has a mechanism to reorganize the data into its internal optimized, compressed and columnar format and stores this optimized data in cloud storage. The data objects are accessible only through SQL query operations run using Snowflake.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

Databand.ai

JUNE 28, 2023

Having a bigger and more specialized data team can help, but it can hurt if those team members don’t coordinate. More people accessing the data and running their own pipelines and their own transformations causes errors and impacts data stability. is a unified data observability platform built for data engineers.

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Knowledge Hut

DECEMBER 21, 2023

Features: HDFS incorporates concepts like blocks, data nodes, node names, etc. The files stored in HDFS are easily accessible. The data to be stored is distributed over multiple machines. Different databases have different patterns of data storage. Pros: Avro stores data in a compact and efficient manner.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

APRIL 20, 2023

The mix of people, procedures, technologies, and systems ensures that the data within a company is reliable, safe, and simple for employees to access. It is a tool used by businesses to protect their data, manage who has access to it, who oversees it, and how to make it available to staff members for everyday usage.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

ProjectPro

FEBRUARY 25, 2022

Once you ingest data into the pipeline, the feature engineering process begins. It stores all the generated features in a feature data repository. It transfers the output of features to the online feature data storage upon completion of each pipeline, allowing for easy data retrieval.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Monte Carlo

JULY 11, 2023

This can involve altering values, suppressing certain data points, or selectively presenting information to support a particular agenda. System or technical errors: Errors within the data storage, retrieval, or analysis systems can introduce inaccuracies.

Data Cleanse 40

Data Cleanse Datasets Data Governance Government 40

Knowledge Hut

SEPTEMBER 29, 2023

The latest Azure exam from Microsoft is structured as follows: Design and implement data storage: Creating and implementing a storage structure, a partition, and a serving layer are tested in this portion (40–45%). Data Scientist: To extract value from data, data scientists execute sophisticated analytics.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

JULY 26, 2023

It is made up of tables that carry data in rows and columns. Data Access Layer: The data access layer function is to create a connection between the application and the database. Apache Cassandra is a well-known columnar database that can handle enormous quantities of data across dispersed clusters.

Database 52

Database NoSQL Telecommunication MongoDB 52

Snowflake

NOVEMBER 29, 2023

In medicine, lower sequencing costs and improved clinical access to NGS technology has been shown to increase diagnostic yield for a range of diseases, from relatively well-understood Mendelian disorders, including muscular dystrophy and epilepsy , to rare diseases such as Alagille syndrome.

Metadata 81

Metadata Healthcare Medical Data Storage 81

Ascend.io

APRIL 12, 2023

It should detect “schema drift,” and may involve operations that validate datasets against source system metadata, for example. In the correct storage. Coming from and being written to the correct physical file system location, database tables and columns, or other types of data storage systems.

Data Pipeline 52

Data Pipeline Data Integration Datasets Data 52

Precisely

JANUARY 25, 2024

Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. You must carefully consider various mainframe functions, including security, system logs, metadata, and COBOL copybooks when moving to the new cloud platform. Best Practice 2. Best Practice 3.

Metadata 69

Metadata Data Governance Relational Database Government 69

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

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. 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

ProjectPro

FEBRUARY 8, 2023

When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. being data exactly matches the classifier, and 0.0 Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

OCTOBER 31, 2016

Assuming initial data size is 600 TB. How will you estimate the number of data nodes (n)? Estimating the hardware requirement is always challenging in Hadoop environment because we never know when data storage demand can increase for a business. Data nodes also maintain a checksum for each block.

Hadoop 52

Hadoop Big Data Utilities NoSQL 52

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. Snowflake hides user data objects and makes them accessible only through SQL queries through the compute layer.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Rockset

DECEMBER 22, 2020

We will also need to store this data in Elasticsearch. Whether you have each of these types of data in one index or separate doesn’t matter as we will be accessing them separately and joining them within our application. Read more about how Rockset compares to Elasticsearch and explore how to migrate to Rockset.

SQL 40

SQL Data MongoDB Aggregated Data 40

Monte Carlo

MAY 30, 2023

It’s designed to improve upon the performance and usability challenges of older data storage formats such as Apache Hive and Apache Parquet. Choose the right partitioning strategy Partitioning can significantly improve query performance by reducing the amount of data scanned.

Metadata 52

Metadata Raw Data Data Lake Data 52

Data Engineering Podcast

FEBRUARY 27, 2022

Batch or streaming (acceptable latencies) Data storage (lake or warehouse) How is the data going to be used? The warehouse (Bigquery, Snowflake, Redshift) has become the focal point of the "modern data stack" Data orchestration Who will be managing the workflow logic?

Designing 100

Designing Metadata Data Lake Relational Database 100

Snowflake

JANUARY 22, 2024

As part of that transition, Fidelity has consolidated its analytics data into its Enterprise Analytics Platform, which is engineered using the Snowflake Data Cloud, making it easier for teams and departments across the company to access the data they need.

Engineering 61

Engineering Data Lake Unstructured Data Metadata 61

Engineering at Meta

OCTOBER 31, 2023

Each represents a class of data — not individual records. SCARF coordinates several kinds of tasks for each data system: metadata collection (e.g., data quantity, field types), usage collection, analysis, and actions. After a configured time, SCARF blocks all reads and writes via a data system specific mechanism.

Data 90

Data Metadata Coding Relational Database 90

Cloudera

SEPTEMBER 15, 2022

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. Diversity of workloads. LEGACY Bucket.

Systems 86

Systems Hadoop Metadata Telecommunication 86

LinkedIn Engineering

JULY 27, 2023

It’s now much easier to manage large infra requirements that have traditionally demanded an amalgamation of teams like DBA, Infra-SRE, Onprem-SMEs, network managers, and access control managers working together. Data connections are secured through Azure Key Vaults and network connectivity is protected by LinkedIn's NACL control.

Metadata 75

Metadata Utilities Cloud Data Lake 75