Smart Data Collective

AUGUST 9, 2022

The issue is that it is difficult to manage data without the right infrastructure. One of the most important things companies need is a database. NoSQL databases are the alternative to SQL databases. What are NoSQL databases and where did they come from? What are the types of NoSQL databases?

Database 119

Database SQL Big Data Big Data 119

Towards AI

APRIL 22, 2024

Items in your shopping carts, comments on all your posts, and changing scores in a video game are examples of information stored somewhere in a database. Which begs the question what is a database? Types of Databases: There are many different types of databases.

Database 109

Database SQL Clustering Big Data 109

Dataconomy

JUNE 10, 2022

The vast majority of data created today is unstructured – that is, it’s information in many different forms that don’t follow conventional data models. That makes it difficult to store and manage in a standard relational database. According to IDC, 80% of all data by 2025.

Database 170

Database Data Modeling Data Models 170

Flipboard

FEBRUARY 14, 2023

Time-varying entities may contain multiple time-varying and static attributes, making mapping them a particular challenge.

Data Modeling 123

Data Modeling Data Models Database Big Data 123

Dataversity

DECEMBER 20, 2021

Reading Larry Burns’ “Data Model Storytelling” (TechnicsPub.com, 2021) was a really good experience for a guy like me (i.e., someone who thinks that data models are narratives). The post Tales of Data Modelers appeared first on DATAVERSITY. The post Tales of Data Modelers appeared first on DATAVERSITY.

Data Modeling 98

Data Modeling Data Models Database SQL 98

Flipboard

JULY 24, 2023

It is also called the second brain as it can store data that is not arranged according to a present data model or schema and, therefore, cannot be stored in a traditional relational database or RDBMS. It can also get back the information that is lost from us with the help of advanced artificial intelligence.

Artificial Intelligence 122

Artificial Intelligence Artificial Intelligence Natural Language Processing Data Science 122

Data Science Dojo

FEBRUARY 9, 2023

From data discovery and cleaning to report creation and sharing, we will delve into the key steps that can be taken to turn data into decisions. A data analyst is a professional who uses data to inform business decisions. Check out this course and learn Power BI today!

Power BI 221

Power BI Data Analyst Data Visualization Data Analysis 221

Dataversity

JANUARY 18, 2021

So, I had to cut down my January 2021 list of things of importance in Data Modeling in this new, fine year (I hope)! The post 2021: Three Game-Changing Data Modeling Perspectives appeared first on DATAVERSITY. Common wisdom has it that we humans can only focus on three things at a time.

Data Modeling 98

Data Modeling Data Models Database SQL 98

phData

JUNE 13, 2023

While the front-end report visuals are important and the most visible to end users, a lot goes on behind the scenes that contribute heavily to the end product, including data modeling. In this blog, we’ll describe data modeling and its significance in Power BI. What is Data Modeling?

Power BI 93

Power BI Data Modeling Data Models Data Warehouse 93

Data Science Dojo

FEBRUARY 23, 2024

You can upload your data files to this GPT that it can then analyze. Once you provide relevant prompts of focus to the GPT, it can generate appropriate data visuals based on the information from the uploaded files. Other than the advanced data analysis, it can also deal with image conversions.

Data Science 253

Data Science Data Analysis Data Analysis Machine Learning 253

Data Science Blog

SEPTEMBER 19, 2023

So why using IaC for Cloud Data Infrastructures? This ensures that the data models and queries developed by data professionals are consistent with the underlying infrastructure. Enhanced Security and Compliance Data Warehouses often store sensitive information, making security a paramount concern.

Data Warehouse 259

Data Warehouse Azure SQL Database 259

Smart Data Collective

MAY 16, 2022

Data management software helps in reducing the cost of maintaining the data by helping in the management and maintenance of the data stored in the database. It also helps in providing visibility to data and thus enables the users to make informed decisions. They are a part of the data management system.

Data Mining 134

Data Mining Data Mining Data Mining Data Warehouse 134

Data Science Dojo

MARCH 7, 2023

As data science evolves and grows, the demand for skilled data scientists is also rising. A data scientist’s role is to extract insights and knowledge from data and to use this information to inform decisions and drive business growth.

Data Scientist 221

Data Scientist Exploratory Data Analysis Data Visualization Data Science 221

Smart Data Collective

AUGUST 12, 2022

Organizations that need servers for their databases or cloud computing can’t just go out and buy the first option that presents itself, though. Random Access Memory will help determine how fast a server can process data in different formats, so you don’t want to skimp on this feature. Type of database. MS SQL Server. PostgreSQL.

Cloud Computing 81

Cloud Computing Database SQL System Architecture 81

Pickl AI

JUNE 28, 2023

Data is driving most business decisions. In this, data modeling tools play a crucial role in developing and maintaining the information system. Moreover, it involves the creation of a conceptual representation of data and its relationship. Data modeling tools play a significant role in this.

Data Modeling 52

Data Modeling Data Models Database SQL 52

Data Science Connect

JANUARY 27, 2023

In this blog post, we will be discussing 7 tips that will help you become a successful data engineer and take your career to the next level. Learn SQL: As a data engineer, you will be working with large amounts of data, and SQL is the most commonly used language for interacting with databases.

Data Engineer 130

Data Engineer Data Engineering Data Engineering Data Engineering 130

Cambridge Intelligence

OCTOBER 25, 2023

Visualizing graph data doesn’t necessarily depend on a graph database… Working on a graph visualization project? You might assume that graph databases are the way to go – they have the word “graph” in them, after all. Do I need a graph database? It depends on your project. Unstructured?

Database 64

Database Data Modeling Data Models Algorithm 64

Towards AI

MARCH 20, 2024

Graph databases and knowledge graphs are among the most widely adopted solutions for managing data represented as graphs, consisting of nodes (entities) and edges (relationships). Knowledge graphs extend the capabilities of graph databases by incorporating mechanisms to infer and derive new knowledge from the existing graph data.

Database 119

Database Data Analysis Data Analysis Data Modeling 119

Data Science Dojo

FEBRUARY 23, 2024

It makes them more versatile as they are not limited to handling textual information, but can process multimodal forms of data. Other data science tasks include data preprocessing, visualization, and statistical analysis. You can upload your data files to this GPT that it can then analyze.

Data Science 195

Data Science Data Analysis Data Analysis Data Analyst 195

IBM Journey to AI blog

AUGUST 7, 2023

Blockchain databases were designed to enhance trust in centralized ecosystems by incorporating tamper-evidence features into traditional databases. However, existing blockchain databases lack efficient tools for multiple parties to control shared data on the ledger.

Database 74

Database Data Governance Data Modeling Data Models 74

Pickl AI

FEBRUARY 23, 2023

Organisations must store data in a safe and secure place for which Databases and Data warehouses are essential. You must be familiar with the terms, but Database and Data Warehouse have some significant differences while being equally crucial for businesses. What is a Database? What is Data Warehouse?

Data Warehouse 52

Data Warehouse Database Data Analysis Data Analysis 52

Cambridge Intelligence

OCTOBER 19, 2023

That’s why our data visualization SDKs are database agnostic: so you’re free to choose the right stack for your application. There have been a lot of new entrants and innovations in the graph database category, with some vendors slowly dipping below the radar, or always staying on the periphery.

Database 59

Database Azure SQL Analytics 59

Data Science Dojo

OCTOBER 31, 2024

Specialized Industry Knowledge The University of California, Berkeley notes that remote data scientists often work with clients across diverse industries. Whether it’s finance, healthcare, or tech, each sector has unique data requirements.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Towards AI

JULY 17, 2024

I’m not going to go into huge details on this as if you follow AI / LLM (which I assume you do if you are reading this) but in a nutshell, RAG is the process whereby you feed external data into an LLM alongside prompts to ensure it has all of the information it needs to make decisions. We use a graph database that is designed for it.

Database 111

Database Data Modeling Data Models SQL 111

Dataversity

JANUARY 16, 2023

In today’s data-driven world, technologies are changing very rapidly, and databases are no exception to this. The current database market offers hundreds of databases, all of them varying in data models, usage, performance, concurrency, scalability, security, and the amount of supplier support provided.

Database 52

Database Data Modeling Data Models 52

Smart Data Collective

OCTOBER 19, 2022

One of the problems companies face is trying to setup a database that will be able to handle the large quantity of data that they need to manage. There are a number of solutions that can help companies manage their databases. They don’t even necessarily need to understand NoSQL to manage their databases.

Big Data 124

Big Data Big Data Database AWS 124

Data Science Dojo

FEBRUARY 23, 2024

It makes them more versatile as they are not limited to handling textual information, but can process multimodal forms of data. Other data science tasks include data preprocessing, visualization, and statistical analysis. You can upload your data files to this GPT that it can then analyze.

Data Science 195

Data Science Data Analysis Data Analysis ML 195

Pickl AI

JULY 8, 2024

Summary: Time series databases (TSDBs) are built for efficiently storing and analyzing data that changes over time. This data, often from sensors or IoT devices, is typically collected at regular intervals. Within this data ocean, a specific type holds immense value: time series data.

Database 52

Database Data Pipeline Machine Learning Machine Learning 52

Pickl AI

OCTOBER 21, 2024

Summary: This article highlights the significance of Database Management Systems in social media giants, focusing on their functionality, types, challenges, and future trends that impact user experience and data management. As businesses increasingly rely on data-driven strategies, the role of a DBMS becomes paramount.

Database 52

Database Apache Kafka Machine Learning Machine Learning 52

phData

JULY 18, 2023

Throughout my analytics journey, I’ve encountered all sorts of data models, from simple to incredibly complex. I’ve also helped everyone, from data newbies and data experts, implement a wide range of solutions in Sigma Computing. Benefits Enhanced flexibility for modeling and data changes.

Data Modeling 52

Data Modeling Data Models Database Data Analysis 52

Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Data Intelligence emerges as the indispensable force steering businesses towards informed and strategic decision-making. These insights?

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

Dataconomy

SEPTEMBER 4, 2023

Cloud analytics is the art and science of mining insights from data stored in cloud-based platforms. By tapping into the power of cloud technology, organizations can efficiently analyze large datasets, uncover hidden patterns, predict future trends, and make informed decisions to drive their businesses forward.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Mlearning.ai

FEBRUARY 13, 2023

Welcome to the wild, wacky world of databases! to the digital world, you’ll find that these unsung heroes of the digital age are essential for keeping your data organised and secure. But with so many types of databases to choose from, how do you know which one is right for you? The most well-known graph database is Neo4j.

Database 52

Database Data Modeling Data Models Big Data 52

phData

SEPTEMBER 19, 2023

However, to fully harness the potential of a data lake, effective data modeling methodologies and processes are crucial. Data modeling plays a pivotal role in defining the structure, relationships, and semantics of data within a data lake. What is a Data Lake?

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Dataversity

OCTOBER 4, 2021

And we have short delivery cycles, sprints, and a lot of peers to share data models with. The post Quick, Easy, and Flexible Data Model Diagrams appeared first on DATAVERSITY. Many of us have a lot to do. In search of something lightweight, which is quick and easy, and may be produced (or consumed) by other programs?

Data Modeling 52

Data Modeling Data Models Database 52

Hacker News

NOVEMBER 14, 2023

OnPrem - Geospatial database D2. OnPrem - SAP database D4. OnCloud - Large mirror database D10. OnPrem - LotusNotes database D11. OnPrem - LotusNotes database D11. OnPrem - IBM BPM database D12. In 2000s many of our systems were built on top of IBM Lotus Notes databases. OnPrem - Sharepoint D7.

Power BI 130

Power BI Database Algorithm Azure 130

Smart Data Collective

JULY 9, 2023

By understanding the power of ETL, organisations can harness the potential of their data and gain valuable insights that drive informed choices. ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse.

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