Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. Almost every modern organization is now a data-generating machine. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Cloudera

JUNE 22, 2023

These dis-integrated resources are “data platforms” in name only: in addition to their high maintenance costs, their lack of interoperability with other critical systems makes it difficult to respond to business change. The top-line benefits of a hybrid data platform include: Cost efficiency. Simplified compliance. Flexibility.

Cost-Benefit 66

Cost-Benefit Digital Transformation Data Governance Unstructured Data 66

AWS Big Data

MARCH 7, 2024

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement. Example Corp.

Data Lake 114

Data Lake Analytics Dashboards Metrics 114

Ontotext

DECEMBER 1, 2023

It enriched their understanding of the full spectrum of knowledge graph business applications and the technology partner ecosystem needed to turn data into a competitive advantage. Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises.

Metadata 78

Metadata Sales Consulting Enterprise 78

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. And where does all this data live?

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

Ontotext

NOVEMBER 22, 2020

Data and content are organized in a way that facilitates discoverability, insights and decision making rather than be bound by limitations of data formats and legacy systems. GraphQL has a number of advantages for developers, especially for data-centric applications. Data silos are as costly as they are inevitable.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

BizAcuity

MAY 10, 2022

Cloud technology and innovation drives data-driven decision making culture in any organization. Cloud washing is storing data on the cloud for use over the internet. Storing data is extremely expensive even with VMs during this time. The platform is built on S3 and EC2 using a hosted Hadoop framework.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

FineReport

APRIL 26, 2023

As the world becomes increasingly digitized, the amount of data being generated on a daily basis is growing at an unprecedented rate. This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. What is Big Data? What is Big Data?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Cloudera

AUGUST 16, 2021

We just announced Cloudera DataFlow for the Public Cloud (CDF-PC), the first cloud-native runtime for Apache NiFi data flows. Apache Nifi is a powerful tool to build data movement pipelines using a visual flow designer. Implementing an automated scale up and scale down procedure for NiFi clusters is complex and time consuming.

Dashboards 122

Dashboards Metrics KPI Data-driven 122

IBM Big Data Hub

JANUARY 16, 2024

Businesses are increasingly embracing data-intensive workloads, including high-performance computing, artificial intelligence (AI) and machine learning (ML). Their activity requires active cooling and management of the data center spaces that they operate in. This metric varies based on the energy source.

IT 86

IT Cost-Benefit Consulting Measurement 86

Cloudera

AUGUST 31, 2020

With data at the heart of its business, SMG has for many years pursued the most cutting-edge data management technologies. As SMG continued to innovate, the scale, variety and velocity of data made its legacy warehouse environment show its limits. The case for a new Data Warehouse? Data-driven Proof of Concept.

Slice and Dice 66

Slice and Dice Management Data Warehouse Analytics 66

bridgei2i

JANUARY 24, 2022

And in this episode, we bring you one such self-driven and ambitious woman who chose her own path. I’m your host, Sushmita Krishnakumar. And today, it’s an honor to host such a talent. Sushmita: So Rajani, you started as a data science practitioner a few years back. Hey, Rajani, welcome to the podcast.

Data Processing 52

Data Processing Data Science Unstructured Data Enterprise 52

datapine

NOVEMBER 19, 2019

No matter if you need to conduct quick online data analysis or gather enormous volumes of data, this technology will make a significant impact in the future. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

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 this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

Sisense

JULY 23, 2021

During this period, those working for each city’s Organising Committee for the Olympic Games (OCOG) collect a huge amount of data about the planning and delivery of the Games. At the Information, Knowledge, and Games Learning (IKL) unit, we anticipate collecting about 1TB of data from primary sources.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

CIO Business Intelligence

AUGUST 1, 2023

But with all the excitement and hype, it’s easy for employees to invest time in AI tools that compromise confidential data or for managers to select shadow AI tools that haven’t been through security, data governance, and other vendor compliance reviews.

Digital Transformation 98

Digital Transformation Unstructured Data Strategy Experimentation 98

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

DataRobot

SEPTEMBER 14, 2021

To provide the ability to integrate diverse data sources. To support the need to connect AI-driven decisions directly with existing business applications and services, like Snowflake, Salesforce, and ServiceNow. We’re building a platform for all users: data scientists, analytics experts, business users, and IT.

Unstructured Data 52

Unstructured Data Data-driven Data Processing Modeling 52