ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

Data Lakes 52

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Flipboard

APRIL 17, 2023

Enterprises often rely on data warehouses and data lakes to handle big data for various purposes, from business intelligence to data science. A new approach, called a data lakehouse, aims to …

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Ocean Protocol

AUGUST 10, 2023

However, to gain such smart recommendations, we sacrifice our data privacy. Such applications leverage data lakes full of our historical user data to provide these smart recommendations. Let’s start automating private business intelligence generation! You might be asking now why this is even beneficial.

Business Intelligence 52

Business Intelligence Business Intelligence Data Lakes Algorithm 52

Data Science Dojo

JULY 6, 2023

Fivetran: Fivetran is a cloud-based data integration platform that simplifies the process of loading data from various sources into a data warehouse or data lake. It offers pre-built connectors for a wide range of data sources, enabling data engineers to set up data pipelines quickly and easily.

Data Engineering 195

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Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

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Dataversity

NOVEMBER 10, 2022

There are several reasons why the notion of semantic layers has reached the forefront of today’s data management conversations. The analyst community is championing the data fabric tenet. The data mesh and data lake house architectures are gaining traction. Data lakes are widely deployed.

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Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. Which one is right for your business? What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications.

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Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 91

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Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

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Dataversity

JANUARY 25, 2023

Over the past few years, enterprise data architectures have evolved significantly to accommodate the changing data requirements of modern businesses. Data warehouses were first introduced in the […] The post Are Data Warehouses Still Relevant?

Data Warehouse 52

Data Warehouse Data Lakes Cloud Computing Data Pipeline 52

Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. It will enable you to quickly transform and load the data results into Amazon S3 data lakes or JDBC data stores.

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Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Tableau 52

Tableau Data Lakes Data Warehouse SQL 52

The Data Administration Newsletter

MAY 31, 2022

As we enter a new cloud-first era, advancements in technology have helped companies capture and capitalize on data as much as possible. Deciding between which cloud architecture to use has always been a debate between two options: data warehouses and data lakes.

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Data Lakes Data Warehouse Data Governance Business Intelligence 52

The Data Administration Newsletter

MARCH 15, 2022

In her groundbreaking article, How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh, Zhamak Dehghani made the case for building data mesh as the next generation of enterprise data platform architecture.

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Data Lakes Data Governance Big Data Big Data 69

Data Science Blog

MARCH 14, 2023

Datenqualität hingegen, wurde zum wichtigen Faktor jeder Unternehmensbewertung, was Themen wie Reporting, Data Governance und schließlich dann das Data Engineering mehr noch anschob als die Data Science. Google Trends – Big Data (blue), Data Science (red), Business Intelligence (yellow) und Process Mining (green).

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Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Amazon Redshift is a fast and widely used data warehouse.

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Data Science Blog

MARCH 3, 2023

Übrigens nicht mehr so stark bei den Data Scientists, auch wenn richtig gute Mitarbeiter ebenfalls rar gesät sind, den größten Bedarf haben Unternehmen eher bei den Data Engineers. Das sind die Kollegen, die die Data Warehouses oder Data Lakes aufbauen und pflegen. appeared first on Data Science Blog.

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IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 52

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. But when it’s dirty, stagnant, or hard to unleash, your business will suffer. Benefits of a Data Lake.

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Data Lakes Data Governance Data Warehouse Business Intelligence 52

Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Ensure that data is clean, consistent, and up-to-date.

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Analytics Analytics Big Data Analytics Big Data Analytics 203

Alation

FEBRUARY 20, 2020

Organizations who are so successful in their adoption of self-service analytics, that their own business intelligence (BI) evangelists worry that they’ve created an analytics “wild west.” When they see a data catalog for the first time, they’re thrilled that a product exists that can govern the west and increase analyst productivity.

Data Lakes 52

Data Lakes Business Intelligence Business Intelligence Analytics 52

ODSC - Open Data Science

JUNE 12, 2023

Then we have some other ETL processes to constantly land the past 5 years of data into the Datamarts. As we learned in the previous section, a Dataflow is a self-service ETL and data preparation layer connecting to various data sources, transforming the data and storing the results in CSV format in Azure Data Lake Gen 2 ( ADLS Gen2 ).

Power BI 52

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Pickl AI

FEBRUARY 21, 2023

Significantly, data mining can help organisations take more vital and active measures to mitigate these risks and prevent potential losses. Effectively, Data Mining leverages Business Intelligence tools and advanced analytics for analysing historical data.

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 52

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. Data warehousing is a vital constituent of any business intelligence operation.

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Data Warehouse Business Intelligence Business Intelligence Database 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 84

Data Science Analytics Analytics Data Scientist 84

Smart Data Collective

AUGUST 7, 2019

New England College talks in detail about the role of big data in the field of business. They have highlighted some of the biggest applications, as well as some of the precautions businesses need to take, such as navigating the death of data lakes and understanding the role of the GDPR. Data management platform.

Analytics 99

Analytics Analytics Big Data Big Data 99

Analytics Vidhya

OCTOBER 6, 2023

In today’s rapidly evolving digital landscape, seamless data, applications, and device integration are more pressing than ever. Enter Microsoft Fabric, a cutting-edge solution designed to revolutionize how we interact with technology.

Analytics 330

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IBM Journey to AI blog

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

AI 77

AI AI Data Warehouse ML 77

Pickl AI

AUGUST 1, 2023

Key Components of Data Engineering Data Ingestion : Gathering data from various sources, such as databases, APIs, files, and streaming platforms, and bringing it into the data infrastructure. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

Data Engineering 52

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ODSC - Open Data Science

JANUARY 18, 2024

ETL (Extract, Transform, Load) This is a core data engineering process for moving data from one or more sources to a destination, typically a data warehouse or data lake. The reason this is an important skill is that ETL is a critical process for data warehousing and business intelligence.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

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Smart Data Collective

NOVEMBER 30, 2020

Many companies have already taken advantage of data automation in their operations. We have talked about many different types of automation in the past, including the automation of data lakes. Let’s take a look at what it could do for your business. What Does Data Automation Do and What Are Its Limitations?

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IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads.

Data Warehouse 57

Data Warehouse Data Engineering Data Engineer Data Engineering 57

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Alation

JANUARY 26, 2023

Lack of data governance can summon a whole range of problems, including: Lack of consistency For data to be useful, it should be consistent across all areas. A field might not be entered in the same way across different departments, which makes the data difficult to find and affects the accuracy of business intelligence (BI).

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ODSC - Open Data Science

JANUARY 30, 2024

Think of it as building plumbing for data to flow smoothly throughout the organization. EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52