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 91

Data Lake Data Warehouse Cloud Unstructured Data 91

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

Snowflake

SEPTEMBER 19, 2023

AI unlocks new data use cases. With the ability to handle unstructured data types and larger volumes of data, AI gives us the tools to tackle more complex, exciting problems. I was looking at some statistic that at any typical company, more than 80% of the data is unstructured.

Machine Learning 95

Machine Learning Unstructured Data Data Analytics Government 95

Precisely

APRIL 30, 2024

Even with all of the technological advances introduced over the past few decades, many of the data creation and management processes used by businesses today are highly manual – meaning they’re slow, ungoverned, and error-prone. These include: Structured data dependence: RPA solutions thrive on well-organized, predictable data.

Unstructured Data 59

Unstructured Data Government Data Validation Programming 59

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 109

IT Unstructured Data Data Architecture Government 109

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

JANUARY 16, 2024

Data issues identified and resolved faster A bright and rapidly evolving future 1. Data lake and data warehouse convergence The data lake vs data warehouse question is constantly evolving. The maxim that data warehouses hold structured data while data lakes hold unstructured data is quickly breaking down.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making.

Unstructured Data 73

Unstructured Data Data Lake Data Architecture Data 73

Knowledge Hut

APRIL 23, 2024

Example of Data Variety An instance of data variety within the four Vs of big data is exemplified by customer data in the retail industry. Customer data come in numerous formats. It can be structured data from customer profiles, transaction records, or purchase history.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Precisely

MARCH 9, 2023

We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data. Precisely helps enterprises manage the integrity of their data.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

DareData

JANUARY 30, 2023

As the field of data science and machine learning continues to evolve, it is increasingly evident that data engineering cannot be separated from it. Gone are the days when organizations could rely on models trained and stored in notebooks without any structure, governance, or testing.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Cloudera

DECEMBER 11, 2020

The Data Security and Governance category, at the annual Data Impact Awards, has never been so important. The sudden rise in remote working, a huge influx in data as the world turned digital, not to mention the never-ending list of regulations businesses need to remain compliant with (how many acronyms can you name in full?

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

Knowledge Hut

APRIL 25, 2024

When done correctly, data integration can enhance data quality, free up resources, lower IT costs, and stimulate creativity without significantly modifying current applications or data structures. Data Governance Data governance is the process of ensuring that data is trustworthy, accurate, available, and usable.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 58

Data Warehouse Unstructured Data Medical Pharmaceutical 58

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 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

Cloudera

OCTOBER 7, 2021

The concept of the data mesh architecture is not entirely new; Its conceptual origins are rooted in the microservices architecture, its design principles (i.e., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g., difficulty to achieve cross-organizational governance model).

Architecture 123

Architecture Metadata Government Kafka 123

Monte Carlo

APRIL 24, 2023

AWS is one of the most popular data lake vendors. AWS Lake Formation offers an alternative for data teams looking for a more structured data lake or data lakehouse solution. The added structure and governance from Dataplex makes BigLake an intriguing data lakehouse option as well.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

MARCH 7, 2024

Factors Considered for Selecting the Best Big Data Analytics Tools There are a few factors to consider when selecting the best big data analytics tool for your organization. The first is the type of data you have, which will determine the tool you need.

Big Data 52

Big Data Data Analytics Data Mining MongoDB 52

Data Engineering Weekly

JUNE 4, 2023

[link] Sponsored: The Evolution of the Customer Data Platform Like the composable approach, The Warehouse Native CDP solves the data silo problem by building around the warehouse, but it deploys the integration, real-time transformation, and activation layers as a connected, governable, and observable end-to-end system.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Monte Carlo

APRIL 1, 2021

As a result, data teams going the the lake or even lakehouse route often struggle to answer critical questions about their data such as: Where does my data live? Data discovery tools and platforms can help. Who has access to it? Image courtesy of Adrian on Unsplash.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Monte Carlo

JUNE 28, 2023

These are the world of data and the data warehouse that is focused on using structured data to answer questions about the past and the world of AI that needs more unstructured data to train models to predict the future.

Data Warehouse 52

Data Warehouse Scala Unstructured Data Government 52

AltexSoft

SEPTEMBER 23, 2021

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. So, it also allows for managing data for various tasks, providing centralized governance and data flow control capabilities. Data lake vs data hub.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

ProjectPro

JANUARY 27, 2023

Data Warehousing - ETL tools and processes can be leveraged to load data into a data warehouse for reporting and analysis. Master Data Management - ETL processes can be leveraged to maintain a single version of truth for key data entities by enforcing data governance, consolidation, and tracking data lineage.

BI 52

BI ETL Tools Retail Healthcare 52

Snowflake

MARCH 30, 2023

Schema drift on a wide table structure needs an ALTER TABLE statement, whereas the tall table structure does not. Raw vault does not dictate how those business process outcomes were calculated at the source system, nor does business vault dictate how the soft rules were calculated based on raw data. Enter Snowpark !

Engineering 83

Engineering Raw Data Data Science Scala 83

Grouparoo

JANUARY 11, 2022

A data warehouse is a unified repository where data from diverse sources undergo aggregation and integration into a usable source of information. To achieve this, a data warehouse will require processes to gather and integrate data, manage data quality, create metadata, and support any regulatory compliance and governance procedures.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Precisely

SEPTEMBER 6, 2023

.” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges. To truly succeed in an increasingly data-driven world, organizations need data governance. The results are clear.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

Monte Carlo

AUGUST 31, 2023

We’ll take a closer look at variables that can impact your data next. Migration to the cloud Twenty years ago, your data warehouse (a place to transform and store structured data) probably would have lived in an office basement, not on AWS or Azure. The only way data can be reliable and trustworthy?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52