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

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

Smart Data Collective

NOVEMBER 25, 2019

More and more often, businesses are using data to drive their decisions — which makes cutting-edge analytics and business intelligence strategies one of the best advantages a company can have. New Avenues of Data Discovery. These new avenues of data discovery will give business intelligence analysts more data sources than ever before.

Business Intelligence 101

Business Intelligence Predictive Analytics Data Collection Internet of Things 101

Cloudera

APRIL 20, 2021

Streaming Analytics is a type of data analysis that processes data streams for real-time analytics. It continuously processes data from multiple streams and performs simple calculations to complex event processing for delivering sophisticated use cases. What are the business challenges with today’s data?

Analytics 92

Analytics Unstructured Data IoT Visualization 92

Cloudera

AUGUST 30, 2018

Consider the following practices that, until recently, were relegated to the R&D department: Data-driven decision making – the collection and analysis of data to guide decisions that improve success. Complicating matters is the increasing focus on data protection and the far-reaching implications of IoT (e.g.

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

bridgei2i

OCTOBER 7, 2020

To catch up, underwriting which typically involved manual involvement in garnering data from documents has to change radically. Sometimes due to excessive volume of data, an underwriter can get confused and is unable to measure risk appropriately. Importance of capturing market data for optimized pricing models.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Cloudera

OCTOBER 5, 2023

Your company collects data from different sources and then you analyze the data to help make the right decisions. Or you are only currently using data for a few use cases and struggle to implement organization wide. Or you are only currently using data for a few use cases and struggle to implement organization wide.

Data-driven 80

Data-driven Enterprise Data Governance Unstructured Data 80

IBM Big Data Hub

SEPTEMBER 19, 2022

Join SingleStore and IBM on September 21, 2022 for our webinar “ Accelerating Real-Time IoT Analytics with IBM Cognos and SingleStore ”. Why real-time analytics matters for IoT systems. IoT systems access millions of devices that generate large amounts of streaming data.

IoT 52

IoT Analytics Data Warehouse Manufacturing 52

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. An efficient big data management and storage solution that AWS quickly took advantage of.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

CIO Business Intelligence

MAY 24, 2022

Data has always been fundamental to business, but as organisations continue to move to Cloud based environments coupled with advances in technology like streaming and real-time analytics, building a data driven business is one of the keys to success. There are many attributes a data-driven organisation possesses.

Data-driven 98

Data-driven Data Lake Data Warehouse Cost-Benefit 98

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data Discovery tools available in the market to take their brand forward.

Business Intelligence 20

Business Intelligence Knowledge Discovery Unstructured Data Software 20

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

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 116

Data Lake Analytics Data Warehouse Machine Learning 116

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

bridgei2i

MAY 7, 2019

The financial industry is undergoing a radical shift that’s being driven by mounting regulation and compliance pressures, changing business models, new competition from FinTechs, and disruptive technologies. Financial sector uses crucial customer data that needs to be handled carefully and without error. Automation.

IoT 40

IoT Unstructured Data Finance Data-driven 40

IBM Big Data Hub

MAY 17, 2023

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. The complexity of the task determines the cost and availability of functions, as well as how data is processed and integrated. The global commercial drone market is projected to grow from USD 8.15

Data Collection 82

Data Collection Visualization Data-driven Unstructured Data 82

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. Building the right data model is an important part of your data strategy. Discover why.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs.

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Modeling 65

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

JANUARY 20, 2023

Topping the list of executive priorities for 2023—a year heralded by escalating economic woes and climate risks—is the need for data driven insights to propel efficiency, resiliency, and other key initiatives. 2] Foundational considerations include compute power, memory architecture as well as data processing, storage, and security.

Analytics 137

Analytics Key Performance Indicator Unstructured Data IoT 137

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. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52