Octopai

MARCH 22, 2023

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

Cost-Benefit 78

Cost-Benefit Data Warehouse Unstructured Data Optimization 78

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them!

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Cloudera

SEPTEMBER 17, 2020

To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle. This platform, including an ad-hoc capable data warehouse service with built-in, easy-to-use visualization, made it easy for anyone to jump in and start experimenting.

Experimentation 80

Experimentation Data Warehouse Dashboards Visualization 80

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats. You can monitor the job progress.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

Cloudera

JANUARY 28, 2022

A decision framework to automate and optimize workload execution. Open and extensible to support new clouds, data types and data services. All in a distributed cloud model that spans multi-public, private & edge clouds. . Here, I’ll provide some guidance on key considerations for a hybrid data cloud.

Slice and Dice 109

Slice and Dice Cost-Benefit Risk Data Governance 109

IBM Big Data Hub

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. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

FineReport

JULY 28, 2021

Business Intelligence describes the process of using modern data warehouse technology, data analysis and processing technology, data mining, and data display technology for visualizing, analyzing data, and delivering insightful information. BI Tools vs. Data Science Tool.

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. However, these wide-ranging data types are typically stored in silos across multiple data stores.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

Sisense

OCTOBER 6, 2020

And, as industrial, business, domestic, and personal Internet of Things devices become increasingly intelligent, they communicate with each other and share data to help calibrate performance and maximize efficiency. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Cloudera

AUGUST 30, 2018

Digital technologies are changing business models, reshaping how companies go-to-market, win new customers and drive new revenue-producing opportunities. How do I get to the next level in the data-driven journey fast enough? How do I meet a growing demand for self-serve BI, while not exploding my data warehouse budgets?

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Sisense

APRIL 9, 2021

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

Sisense

MAY 28, 2020

“Not only do they have to deal with data that is distributed across on-premises, hybrid, and multi-cloud environments, but they have to contend with structured, semi-structured, and unstructured data types.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

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 57

Data Warehouse Unstructured Data Analytics Visualization 57

IBM Big Data Hub

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? That’s where the foundation model enters the picture.

Modeling 60

Modeling Cost-Benefit Data Lake Machine Learning 60

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. Azure Data Factory.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

IBM Big Data Hub

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics. What is watsonx.data?

Data Warehouse 79

Data Warehouse Cost-Benefit Recreation/Entertainment Unstructured Data 79

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Monte Carlo Data — Data reliability delivered.

Testing 307

Testing Machine Learning Consulting Data Quality 307

CIO Business Intelligence

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

Cloudera

OCTOBER 29, 2020

At Cloudera, we set out to directly address these lifecycle challenges through the Cloudera Data Platform (CDP) — the only hybrid-cloud, multi-cloud enterprise data platform built for the full data lifecycle. . Over the past months, we’ve been busy innovating and optimizing how teams across the lifecycle work together.

Visualization 105

Visualization Machine Learning Dashboards Data Warehouse 105

FineReport

JUNE 24, 2021

Business intelligence can assist decision-making and operation optimization, either at the operational or tactical, or strategic levels. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

Cloudera

AUGUST 20, 2021

Analytical Outcome: CDP delivers multiple analytical outcomes including, to name a few, operational dashboards via the CDP Operational Database experience or ad-hoc analytics via the CDP Data Warehouse to help surface insights related to a business domain. A Holistic Visual Exploration of Data.

Strategy 94

Strategy Cost-Benefit Visualization Data Warehouse 94

Cloudera

AUGUST 31, 2020

Given the prohibitive cost of scaling it, in addition to the new business focus on data science and the need to leverage public cloud services to support future growth and capability roadmap, SMG decided to migrate from the legacy data warehouse to Cloudera’s solution using Hive LLAP. The case for a new Data Warehouse?

Slice and Dice 62

Slice and Dice Management Data Warehouse Analytics 62

IBM Big Data Hub

MAY 17, 2023

The data captured by the sensors and housed in the cloud flow into real-time monitoring for 24/7 visibility into your assets, enabling the Predictive Failure Model. DaaS uses built-in deep learning models that learn by analyzing images and video streams for classification.

Data Collection 83

Data Collection Visualization Data-driven Unstructured Data 83

Sisense

JUNE 30, 2020

In this diagram , visual analytics is shown to be the foundation for interactive data, thereby demonstrating how the two are connected. Analytics acts as the source for data visualization and contributes to the health of any organization by identifying underlying models and patterns and predicting needs.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. In other words, using metadata about data science work to generate code. Introduction. BTW, videos for Rev2 are up: [link]. SQL and Spark.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

Cloudera

AUGUST 21, 2020

Perhaps one of the most significant contributions in data technology advancement has been the advent of “Big Data” platforms. Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. Streaming data analytics. . There it is.

Cost-Benefit 71

Cost-Benefit Big Data ROI Risk 71

Occam's Razor

NOVEMBER 5, 2007

The fact that to make optimal decisions on the web I was going to have to be comfortable with multiple sources of data, all valuable and all necessary to win. The strategy, for me, was two fold: Go figure out what sources of data, web and non-web, were needed to make decisions. It was totally worth it.

Analytics 98

Analytics Experimentation Metrics Measurement 98