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. Unlike traditional storage solutions, data lakes can handle data at scales from terabytes to petabytes and beyond.

Data Management 52

Data Management Data Lake Management Data Governance 52

Precisely

APRIL 17, 2023

Data quality and consistency, for example, are essential prerequisites for trusted data-driven decisions. Privacy and security are increasingly under the spotlight, driving an increased focus on regulatory compliance and data governance. Data quality remains a top concern for many enterprises.

Data Governance 57

Data Governance Government Data Data Integration 57

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. 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

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. 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

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. Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

Precisely

DECEMBER 19, 2022

. #5 Let’s Talk Real Estate Data The real estate industry has experienced massive innovation and transformation over the past two decades, most of which has been driven by the internet and associated communications technologies. Internal structured data alone is not sufficient – an incomplete database is ineffective.

Data Governance 52

Data Governance Retail Government High Quality Data 52

Knowledge Hut

APRIL 23, 2024

Big Data Training online courses will help you build a robust skill-set working with the most powerful big data tools and technologies. Big Data vs Small Data: Velocity Big Data is often characterized by high data velocity, requiring real-time or near real-time data ingestion and processing.

Big Data 52

Big Data Datasets Data Analysis Media 52

Knowledge Hut

APRIL 25, 2024

It refers to gathering and processing sizable amounts of data to produce insights that may be used by an organization to improve its various facets. Due to this, businesses from a variety of industries are concentrating on implementing this technology. The only component of this huge data analytics is data analytics.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

AltexSoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Cloudera

SEPTEMBER 29, 2021

Forced to adapt to changes in the business landscape and customer behavior, businesses have adopted more digital tools and technologies to drive innovation and increase resilience. . This has made it imperative for governments to leverage digital technologies to become more agile and innovative and better serve their citizens. .

Medical 81

Medical Government Hospitality Electronics 81

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

OCTOBER 30, 2023

The work of a Power BI developer is to take data in its raw form, derive meaning, and make sense of it. They dissect data to see patterns, trends, outliers, etc., using business intelligence tools and collaborate with the technology team and developers to build effective solutions. Excel, SharePoint, and web services.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Knowledge Hut

JULY 24, 2023

Get ready to discover fascinating insights, uncover mind-boggling facts, and explore the transformative potential of cutting-edge technologies like blockchain, cloud computing, and artificial intelligence. Disruptive Database Technologies All existing and upcoming businesses are adopting innovative ways of handling data.

Database 52

Database NoSQL Management Relational Database 52

Monte Carlo

SEPTEMBER 27, 2023

And, since we’re optimistic about the potential for heading off data issues before they cause this kind of headline-generating damage, we’ve also provided three best practices to help your team improve data quality across the organization. But disastrous data quality issues are not unavoidable. But first, the schadenfreude.

Data Governance 52

Data Governance Government Data Data Pipeline 52

Snowflake

SEPTEMBER 19, 2023

With all the hoopla around AI, there’s a lot to get up to speed on—especially the implications this technology has for data analytics. Ahmad has not only witnessed the emergence of AI in the data space but helped shape it throughout his career. We’ve been doing analytics on structured data only.

Machine Learning 95

Machine Learning Unstructured Data Data Analytics Government 95

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

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Ascend.io

JULY 19, 2023

In this article, we provide practical, actionable steps to kick-start your data mesh implementation using the well-established approach of managing People, Processes, and Technology. Consider this your primer to stop overthinking, start acting, and truly harness the power of data mesh. Establish clear data governance policies.

Data Governance 40

Data Governance Government Metadata Data 40

Cloudera

DECEMBER 11, 2020

Based in Germany, Merck KGaA is one of the leading science and technology companies, operating across healthcare, life science, and performance materials business areas. From advancing gene-editing technologies and discovering unique ways to treat the most challenging diseases, to enabling the intelligence of devices.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

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

Knowledge Hut

APRIL 23, 2024

It highlights the importance of handling data in real-time or near-real-time to extract timely insights and enable swift actions. Regarding gathering in relation to velocity, it involves the pace at which data is collected or received. Customer data come in numerous formats.

Big Data 52

Big Data Media Datasets Unstructured Data 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

DareData

JANUARY 30, 2023

At a critical part of a data ingestion process is the data pipeline , a series of steps that are used to gather, transform, and store data. They can be simple or complex, and they can involve multiple steps, technologies or formats such as CSV, Tabular or JSON formats.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

JULY 26, 2023

These datasets typically involve high volume, velocity, variety, and veracity, which are often referred to as the 4 v's of Big Data: Volume: Volume refers to the vast amount of data generated and collected from various sources. Managing and analyzing such large volumes of data requires specialized tools and technologies.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. A data warehouse implies a certain degree of preprocessing, or at the very least, an organized and well-defined data model.

Data Lake 57

Data Lake Data Warehouse Hadoop Raw Data 57

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

Cloudera

OCTOBER 7, 2021

Within the context of a data mesh architecture, I will present industry settings / use cases where the particular architecture is relevant and highlight the business value that it delivers against business and technology areas. need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Architecture 124

Architecture Metadata Government Kafka 124

Snowflake

JANUARY 23, 2023

Data integration and modeling was one of the top capabilities identified when Snowflake analyzed usage patterns of over 6,000 active customers to understand just how marketing teams were using the Data Cloud to modernize their marketing efforts.

Data Integration 57

Data Integration Data Data Warehouse Business Analyst 57

Monte Carlo

MARCH 18, 2021

Challenge #2: Organizational bottlenecks Even if you have well-structured data in place, you need to have the right people with the right skill sets on the right teams to make use of it. Implementing a data governance strategy at your company? And what actions will you empower business leaders to take based on your work?

Data Governance 52

Data Governance Government Machine Learning Datasets 52

Snowflake

APRIL 20, 2023

Snowgrid: Cross-Cloud Data Governance Allow masked columns as inputs to row access policies and conditional masking policies – general availability (GA) Advanced use cases require a masked column in a mapping table to be used as input to a row access policy for row-level authorization. Intellizence Intellizence, Inc.,

Medical 57

Medical Retail Python Pharmaceutical 57

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. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

AltexSoft

MARCH 30, 2023

The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. Besides that, it’s fully compatible with various data ingestion and ETL tools.

Scala 64

Scala Data Lake BI Google Cloud 64

AltexSoft

AUGUST 22, 2022

Gartner claims that there is such a solution capable of enabling companies to have advanced, flexible, and reusable data management across all environments. The solution is called a data fabric. The self-service functionally allows the entire organization to find relevant data faster and gain valuable insights. API support.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

phData: Data Engineering

JULY 18, 2023

Yet, those that do achieve this level of maturity from their data stack are able to unlock breakthrough successes while leaving competitors years behind in innovation. Perhaps the largest roadblock of this data-driven utopia is the continued reliance on a patchwork of legacy, on-premise technologies like Teradata, Netezza, Oracle, etc.,

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

U-Next

SEPTEMBER 29, 2022

There is no guarantee that a company has a data-driven culture or is data-driven merely because it collects a great deal of data. In order to make informed decisions, organizations need to leverage data. . Types of Data in an Organization . A structured data record consists of a very fixed field of data.

Management 52

Management Unstructured Data Data 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

Monte Carlo

JULY 10, 2023

Incomplete data from external sources When you ingest data from an external source, you lack a certain amount of control over how data is structured and made available. Different sources may structure data inconsistently, which can lead to missing values within your data sets.

Data Collection 40

Data Collection Data Governance Government Data 40