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 analytics case study: SkullCandy.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

CIO Business Intelligence

MARCH 24, 2023

A framework for managing data 10 master data management certifications that will pay off Big Data, Data and Information Security, Data Integration, Data Management, Data Mining, Data Science, IT Governance, IT Governance Frameworks, Master Data Management

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

JANUARY 24, 2024

Building a successful data strategy at scale goes beyond collecting and analyzing data,” says Ryan Swann, chief data analytics officer at financial services firm Vanguard. What’s the point of investing time and money on a strategy that lacks focus?

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

FineReport

JUNE 24, 2021

Once the data becomes more extensive or more complex, Excel or other simple solutions may “fetter” your potentialities. That’s why business intelligence solutions(BI solutions) come into our minds. Business Intelligence Solutions Definition. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

AWS Big Data

FEBRUARY 7, 2023

In the data analytics space, organizations often deal with many tables in different databases and file formats to hold data for different business functions. In this post, we implement an architecture to build a transactional data lake built on the aforementioned Hudi features.

Data Lake 70

Data Lake Testing Big Data Structured Data 70

CIO Business Intelligence

JUNE 23, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 96

IT Data Architecture Unstructured Data Big Data 96

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021.

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

CIO Business Intelligence

JUNE 28, 2022

Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

Management 138

Management Internet of Things Statistics Data-driven 138

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. 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.

Data Lake 118

Data Lake Unstructured Data Data Warehouse Data Quality 118

FineReport

DECEMBER 27, 2021

Modern enterprise business intelligence (BI) tools and practices enable quick decision making. Indeed, Early action on insights allows businesses to identify internal trends and improve inefficiencies. Furthermore, It is important to note that the advantages of business intelligence vary by industry and application.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

FineReport

JULY 18, 2022

There exists a variety of data analysis tools for you to choose from. In order to assist you in selecting the one that best fits your company’s needs, let’s examine several best data analytics tools that are popular in 2022. How to Choose Data Analysis Tools. Finally, the budget can not be ignored.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

datapine

MAY 27, 2020

In recent years, analytical reporting has evolved into one of the world’s most important business intelligence components, compelling companies to adapt their strategies based on powerful data-driven insights. How To Write An Analytical Report? Try our professional reporting software for 14 days, completely free!

Reporting 245

Reporting Analytics Dashboards Sales 245

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 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. The right data model + artificial intelligence = augmented analytics.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

JANUARY 22, 2024

The majority of data produced by these accounts is used downstream for business intelligence (BI) purposes and in Amazon Athena , by hundreds of business users every day. The solution Acast implemented is a data mesh, architected on AWS. Srikant Das is an Acceleration Lab Solutions Architect at Amazon Web Services.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

CDW Research Hub

APRIL 28, 2020

Automate data loads with job scheduling so that your data is always there when you need it. Quickly access data for business intelligence, reporting and visualization, or access next-generation analytics platforms like ThoughtSpot. Use Matillion’s universal REST API to connect to any AP-enabled application.

Data-driven 52

Data-driven Analytics Consulting ROI 52

CDW Research Hub

DECEMBER 4, 2019

Cloud-based data warehouses can also perform complex analytical queries much faster due to the use of massively parallel processing (MPP), which uses multiple processors—each with its own operating system and memory—to simultaneously perform a set of coordinated computations.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

CIO Business Intelligence

JUNE 14, 2023

Consider data types. How is it possible to manage the data lifecycle, especially for extremely large volumes of unstructured data? Unlike structured data, which is organized into predefined fields and tables, unstructured data does not have a well-defined schema or structure.

Unstructured Data 64

Unstructured Data IT Manufacturing Visualization 64

AWS Big Data

DECEMBER 21, 2023

For the downstream consumption by all departments across the organization, smava’s Data Platform team prepares curated data products following the extract, load, and transform (ELT) pattern. Finally, the data is aggregated into specific data products oriented to a specific business line.

Data Lake 85

Data Lake Data Warehouse Data-driven B2B 85

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52