CIO Business Intelligence

APRIL 25, 2022

Now generally available, the M&E data lakehouse comes with industry use-case specific features that the company calls accelerators, including real-time personalization, said Steve Sobel, the company’s global head of communications, in a blog post. Features focus on media and entertainment firms.

Recreation/Entertainment 109

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 109

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 83

Data Lake Big Data Consulting Data Warehouse 83

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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. Learn more about the benefits of data fabric and IBM Cloud Pak for Data.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Andrew White

DECEMBER 9, 2019

And don’t start with a focus on domain specific data. See: Webinar Effective Data and Analytics Governance – Finally! Blog A Little Data Governance Goes a Long Way. I spoke with an IT software vendor about an aspect of data and analytics governance. Scope could be: Data (i.e. Images (i.e.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

Sisense

APRIL 9, 2021

The amount of data being generated and stored every day has exploded. Companies of all kinds are sitting on stockpiles of data that could someday prove valuable. 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.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

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. Qualitative data benefits: Unlocking understanding.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

JANUARY 8, 2024

Therefore, it is critical for organizations to embrace a low-latency, scalable, and reliable data streaming infrastructure to deliver real-time business applications and better customer experiences. Stream ingestion – The stream ingestion layer is responsible for ingesting data into the stream storage layer.

Analytics 111

Analytics IoT Data-driven Snapshot 111

IBM Big Data Hub

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. Everybody wins with a data catalog.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

SEPTEMBER 21, 2023

Enterprises still aren’t extracting enough value from unstructured data hidden away in documents, though, says Nick Kramer, VP for applied solutions at management consultancy SSA & Company. Data warehouses then evolved into data lakes, and then data fabrics and other enterprise-wide data architectures.

Enterprise 127

Enterprise Consulting Modeling Cost-Benefit 127

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

BizAcuity

MAY 10, 2022

And how this transformation will impact businesses in the short and long run is the main discussion in this blog. 2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. More on Kubernetes soon.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

BizAcuity

APRIL 14, 2022

The best way to avoid poor data quality is having a strict data governance system in place. The majority of the data a business has stored is generally unstructured. Most of these are accumulated in data silos or data lakes. Which means queries for large data sets might take days or eventually fail.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Cloudera

SEPTEMBER 12, 2022

Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. And second, for the data that is used, 80% is semi- or unstructured. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse.

Unstructured Data 72

Unstructured Data Data Architecture Data Lake Snapshot 72

IBM Big Data Hub

AUGUST 1, 2023

models are trained on IBM’s curated, enterprise-focused data lake. Fortunately, data stores serve as secure data repositories and enable foundation models to scale in both terms of their size and their training data. Foundation models focused on enterprise value IBM’s watsonx.ai All watsonx.ai

Modeling 60

Modeling Cost-Benefit Data Lake Machine Learning 60

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. How do spreadsheet users benefit from Alation Connected Sheets ?

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive. Data modeling: Create relationships between data.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Metadata 97

Metadata Machine Learning Unstructured Data Data Lake 97

Cloudera

MAY 16, 2018

This example combines three types of unrelated data: Legal entity data: Two companies with completely unrelated business lines (coffee and waste management) merged together; Unstructured data: Fraudulent promotion campaigns took place through press releases and a fake stock-picking robot.

Data Lake 41

Data Lake Risk Visualization Unstructured Data 41

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 74

Data Quality Testing Data Warehouse Unstructured Data 74

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. But the “elephant in the room” is NOT ‘Hadoop’.

Cost-Benefit 73

Cost-Benefit Big Data ROI Risk 73

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. This design philosophy was adapted from our friends at Fishtown Analytics.).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

JULY 6, 2021

To drive this point home, Yonatan Dolan, an Analytics Specialist from AWS, introduced AWS’ new Lake House architecture. This cutting-edge service integrates the abilities of a data lake, a data warehouse, and purpose-built stores, to enable unified governance and easy data movement.

Data Lake 52

Data Lake Data Warehouse Data-driven Unstructured Data 52

Alation

AUGUST 4, 2022

And where data was available, the ability to access and interpret it proved problematic. Big data can grow too big fast. Left unchecked, data lakes became data swamps. Some data lake implementations required expensive ‘cleansing pumps’ to make them navigable again. Subscribe to Alation's Blog.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. Subscribe to Alation's Blog. The post What Is Data Modernization?

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52