Databand.ai

JULY 19, 2023

Data lineage tools are not a new concept. However, their importance has grown significantly in recent years due to the increasing complexity of data architectures and the growing need for data governance and compliance. In this article: Why Are Data Lineage Tools Important?

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Monte Carlo

APRIL 24, 2023

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. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. This privacy law must be kept in mind when building data architecture.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Data Engineering Podcast

SEPTEMBER 14, 2020

Tree Schema is a data catalog that is making metadata management accessible to everyone. With Tree Schema you can create your data catalog and have it fully populated in under five minutes when using one of the many automated adapters that can connect directly to your data stores.

Process 100

Process Unstructured Data Metadata Data Engineering 100

Snowflake

JANUARY 26, 2023

Accessing data from the manufacturing shop floor is one of the key topics of interest with the majority of cloud platform vendors due to the pace of Industry 4.0 requires multiple categories of data, from time series and transactional data to structured and unstructured data. Industry 4.0, By leveraging I4.0

Data Ingestion 52

Data Ingestion Manufacturing Unstructured Data Architecture 52

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

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 82

Data Lake Analytics Application Cloud Storage Architecture 82

Knowledge Hut

SEPTEMBER 29, 2023

The Azure Data Engineer Certification test evaluates one's capacity for organizing and putting into practice data processing, security, and storage, as well as their capacity for keeping track of and maximizing data processing and storage. They control and safeguard the flow of organized and unstructured data from many sources.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

AltexSoft

OCTOBER 18, 2022

Medical data labeling. Medical or not, unstructured data — like texts, images, or audio files — require labeling or annotation to train machine learning models. This process involves adding descriptive elements — tags — to pieces of data so that a computer could understand what the image or text is about.

Medical 52

Medical Datasets Machine Learning Hospitality 52

Cloudera

AUGUST 30, 2018

Consider the following practices that, until recently, were relegated to the R&D department: Data-driven decision making – the collection and analysis of data to guide decisions that improve success. For more on the data-driven journey, I would encourage you to view our Cloudera Now presentation.

Unstructured Data 40

Unstructured Data Machine Learning Data Warehouse BI 40

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 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 83

Metadata Healthcare Medical Data Storage 83

Snowflake

NOVEMBER 2, 2023

Use cases change, needs change, technology changes – and therefore data infrastructure should be able to scale and evolve with change. We’re committed to giving customers a choice and the ability to adapt while maintaining our core tenets of strong security and governance, excellent performance and simplicity.

Data Lake 90

Data Lake Data Warehouse Cloud Unstructured Data 90

Monte Carlo

AUGUST 25, 2023

One advantage of data warehouses is their integrated nature. As fully managed solutions, data warehouses are designed to offer ease of construction and operation. A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

NOVEMBER 17, 2022

We needed a solution to manage our data at scale, to provide greater experiences to our customers. With Cloudera Data Platform, we aim to unlock value faster and offer consistent data security and governance to meet this goal. Aqeel Ahmed Jatoi, Lead – Architecture, Governance and Control, Habib Bank Limited.

Banking 84

Banking Management Data Lake Professional Services 84

Monte Carlo

NOVEMBER 6, 2023

They can range in terms of complexity, ease of use, and feature sets, but all are designed to help illuminate the dark corners of your data repositories, and are a critical component of your data governance practice. Here’s an overview of ten popular data discovery tools (in no particular order) that are available today.

Metadata 40

Metadata Unstructured Data Government Data Governance 40

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. Historically, the platform was housed in physical servers.

Engineering 63

Engineering Data Lake Unstructured Data Metadata 63

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Who has access to it?

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Towards Data Science

FEBRUARY 9, 2024

Data Store Another significant change from 2021 to 2024 lies in the shift from “Data Warehouse” to “Data Store,” acknowledging the expanding database horizon, including the rise of Data Lakes. Without an orchestration engine, the ability to modularize your data platform and unlock its full potential is limited.

Building 78

Building Transportation Data Lake Metadata 78

AltexSoft

JUNE 26, 2023

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) Dive deeper into the subject by reading our article Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

SEPTEMBER 9, 2022

Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Iceberg handles massive data born in the cloud.

Architecture 101

Architecture Metadata Unstructured Data Machine Learning 101

Monte Carlo

MAY 31, 2022

Metadata from the data warehouse/lake and from the BI tool of record can then be used to map the dependencies between the tables and dashboards. Spark lineage is the metadata detailing the journey data takes across its lifecycle including source, creator, transformations, and related data sets.

Data Lake 52

Data Lake Building Scala Metadata 52

AltexSoft

AUGUST 22, 2022

So, instead of replacing or rebuilding the existing infrastructure, you add a new, ML-powered abstraction layer on top of the underlying data sources, enabling various users to access and manage the information they need without duplication. Data fabric architecture example. Unified data access. Data and metadata.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Traditional data warehouse platform architecture. Poor data quality, reliability, and integrity. Key features of a data lakehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

SEPTEMBER 23, 2021

With a data hub, businesses receive the means to structure, and harmonize information collected from various sources. A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. Data lake vs data hub. Data hub architecture.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69

AltexSoft

NOVEMBER 1, 2023

GPEs represent countries, cities, states, or any other regions with a defined boundary or governance. NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data. Once trained, the model can then predict or annotate named entities in raw, unlabeled data.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

ProjectPro

AUGUST 11, 2021

The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. The RDBMS can either be directly accessed from the data warehouse layer or stored in data marts designed for specific enterprise departments.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

AltexSoft

JULY 29, 2022

According to the latest report by Allied Market Research , the Big Data platform will see the biggest rise in adoption in telecommunication, healthcare, and government sectors. Instruments like Apache ZooKeeper and Apache Oozie help better coordinate operations, schedule jobs, and track metadata across a Hadoop cluster.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Snowflake

MARCH 30, 2023

Automation , because the same loader patterns are used for both and the same metadata tags are expected from both, meaning the applied date timestamp in the business vault will match up with the raw date timestamp where it came from. Data governance As a data management framework, feature stores must consider data privacy and data governance.

Engineering 83

Engineering Raw Data Data Science Scala 83

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

OCTOBER 20, 2021

AutoKeras focuses on making machine learning and deep learning more accessible with the help of Neural Architecture Search. Auto-Weka : Weka is a top-rated java-based machine learning software for data exploration. On that note, what is AI governance? AI Governance is a necessary evil. Facebook's wit.ai

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

Cloudera

SEPTEMBER 6, 2018

It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data. It also supports a number of frameworks that can process data in parallel, in batch or in streams, in a variety of languages. The foundation of this end-to-end AML solution is Cloudera Enterprise.

Banking 40

Banking Machine Learning Big Data Scala 40