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

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Analytics and intelligence for business users and user adoption.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

Anmut

MARCH 24, 2022

A closer look at the importance (and transformational value) of your organisation’s data landscape. After decades in the background, data is currently king of the business world. Over 70% of digital transformations fail, and most CDOs last less than two-and-half years. What is a data landscape?

ROI 52

ROI Measurement Data-driven Data Transformation 52

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

JULY 25, 2023

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Prerequisites To complete the integration, you need a Redshift Serverless data warehouse.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

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

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 111

Data Lake Analytics Data Warehouse Machine Learning 111

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 127

Analytics Machine Learning Software Data mining 127

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 106

Management Metadata Analytics Dashboards 106

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. The data in the machine-readable files can provide valuable insights to understand the true cost of healthcare services and compare prices and quality across hospitals.

Visualization 97

Visualization Dashboards Data-driven Gap analysis 97

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. A metadata management framework does the same for your data analysts.

Metadata 52

Metadata Management Data Governance Machine Learning 52

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 89

Data Lake Analytics Snapshot Optimization 89

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 143

Data Transformation Data-driven Data Strategy Strategy 143

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

AWS Big Data

NOVEMBER 7, 2023

The most impactful data-driven insights come from connecting the dots between all your data sources—across departments, services, on-premises tools, and third-party applications. But typically, connecting data requires complex extract, transform, and load (ETL) pipelines, taking hours or days.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

Ontotext

FEBRUARY 12, 2024

In the final part of this three-part series, we’ll explore ho w data mesh bolsters performance and helps organizations and data teams work more effectively. Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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 93

Analytics Data Lake Metadata Cost-Benefit 93

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 87

Data Lake Data Transformation Cost-Benefit Data-driven 87

IBM Big Data Hub

JUNE 15, 2023

There’s no debate that the volume and variety of data is exploding and that the associated costs are rising rapidly. The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Enter the open data lakehouse.

Data Warehouse 87

Data Warehouse Data Lake Optimization Data-driven 87

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

AWS Big Data

DECEMBER 21, 2023

This is a guest post co-written by Alex Naumov, Principal Data Architect at smava. smava believes in and takes advantage of data-driven decisions in order to become the market leader. smava believes in and takes advantage of data-driven decisions in order to become the market leader.

Data Lake 90

Data Lake Data Warehouse Data-driven B2B 90

DataKitchen

JANUARY 23, 2023

What is data lineage? Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. It is used to understand the provenance of data and how it is transformed and to identify potential errors or issues. What about DataOps Observability? How does it compare?

Testing 130

Testing Data Governance Data Quality Data-driven 130

Jet Global

APRIL 24, 2024

In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your data analysis? How does AI impact analytics and how do you get started? Forget the one-size-fits-all approach.

Business Intelligence 52

Business Intelligence Dashboards Software Reporting 52

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 1, 2023

By leveraging data analysis to solve high-value business problems, they will become more efficient. This is in contrast to traditional BI, which extracts insight from data outside of the app. that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52