AWS Big Data

OCTOBER 11, 2023

Organizations with legacy, on-premises, near-real-time analytics solutions typically rely on self-managed relational databases as their data store for analytics workloads. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

Management 104

Management Metadata Analytics Dashboards 104

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

Sisense

DECEMBER 12, 2019

Building a data-driven business includes choosing the right software and implementing best practices around its use. Our Business Perspectives help you make smarter decisions no matter where you are in your analytics journey. Analyzing large, growing data sets is an urgent demand; it’s an emergency!

Business Intelligence 88

Business Intelligence Software Data-driven Visualization 88

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

FEBRUARY 26, 2020

We all know that data is becoming more and more essential for businesses, as the volume of data keeps growing. Dresner reported that nearly 97% of respondents in their Big Data Analytics Market Study consider Big Data to be either important or critical to their businesses. They’re right.

Digital Transformation 90

Digital Transformation Analytics Cost-Benefit Data-driven 90

Smart Data Collective

APRIL 29, 2020

As the world is gradually becoming more dependent on data, the services, tools and infrastructure are all the more important for businesses in every sector. Data management has become a fundamental business concern, and especially for businesses that are going through a digital transformation.

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications.

Data Lake 83

Data Lake Data Transformation Cost-Benefit Data-driven 83

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 85

Data Lake Analytics Snapshot Optimization 85

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

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. Microsoft. Azure Analysis Services.

Data Lake 115

Data Lake Analytics Data Warehouse Machine Learning 115

Jet Global

MAY 1, 2023

We hope this guide will transform how you build value for your products with embedded analytics. Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. This is in contrast to traditional BI, which extracts insight from data outside of the app.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 129

Analytics Machine Learning Software Data Quality 129

Alation

JUNE 28, 2022

Collecting and using data to make informed decisions is the new foundation for businesses. The key term here is usable : Anyone can be data rich, and collect vast troves of data. This is where metadata, or the data about data, comes into play. What is a Metadata Management Framework?

Metadata 52

Metadata Management Data Governance Machine Learning 52

CIO Business Intelligence

JUNE 14, 2022

For years, IT and data leaders have been striving to help their companies become more data driven. But technology investment alone is not enough to make your organization data driven. A lot of organizations have tried to treat data as a project,” says Traci Gusher, EY Americas data and analytics leader. “It

Data Transformation 144

Data Transformation Data-driven Data Strategy Strategy 144

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices.

Analytics 95

Analytics Data Lake Metadata Cost-Benefit 95