CIO Business Intelligence

MAY 24, 2022

Just after launching a focused data management platform for retail customers in March, enterprise data management vendor Informatica has now released two more industry-specific versions of its Intelligent Data Management Cloud (IDMC) — one for financial services, and the other for health and life sciences.

Finance 139

Finance Management Metadata Data Quality 139

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

AWS Big Data

MARCH 25, 2024

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

Data Lake 91

Data Lake Unstructured Data Management Modeling 91

erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. A sample data warehousing project.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

Cloudera

SEPTEMBER 17, 2020

Today’s data tool challenges. By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. .

Experimentation 80

Experimentation Data Warehouse Dashboards Visualization 80

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Cloudera

SEPTEMBER 15, 2022

Cloudera Contributor: Mark Ramsey, PhD ~ Globally Recognized Chief Data Officer. July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. Luke: What is a modern data platform?

Data Lake 78

Data Lake Data Architecture Data-driven Data Warehouse 78

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. Almost every modern organization is now a data-generating machine. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 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 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

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

erwin

JUNE 26, 2020

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations need a data catalog because it enables them to create a seamless way for employees to access and consume data and business assets in an organized manner. Three Types of Metadata in a Data Catalog.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

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

Sisense

MAY 28, 2020

In the Clouds is where we explore the ways cloud-native architecture, cloud data storage, and cloud analytics are changing key industries and business practices, with anecdotes from experts, how-to’s, and more to help your company excel in the cloud era. The world of data is constantly changing and speeding up every day.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

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.

Data Lake 115

Data Lake Analytics Data Warehouse Machine Learning 115

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 94

Data-driven Data Lake Data Warehouse Cost-Benefit 94

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

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

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. Considering solutions for real-time analytics on IoT data.

IoT 52

IoT Analytics Data Warehouse Manufacturing 52

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. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. Data visualization: painting a picture of your data.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

AUGUST 31, 2020

With data at the heart of its business, SMG has for many years pursued the most cutting-edge data management technologies. As SMG continued to innovate, the scale, variety and velocity of data made its legacy warehouse environment show its limits. The case for a new Data Warehouse?

Slice and Dice 62

Slice and Dice Management Data Warehouse Analytics 62

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

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

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

IBM Big Data Hub

MAY 9, 2023

IBM today announced it is launching IBM watsonx.data , a data store built on an open lakehouse architecture, to help enterprises easily unify and govern their structured and unstructured data, wherever it resides, for high-performance AI and analytics.

Data Warehouse 76

Data Warehouse Cost-Benefit Recreation/Entertainment Unstructured Data 76

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

Sisense

MAY 28, 2019

2019 can best be described as an era of modern cloud data analytics. Convergence in an industry like data analytics can take many forms. We have seen industry rollups in which firms create a collection of analytical tools under one brand. To see a BI vendor doubling down on in-data technology isn’t surprising.

Data Analytics 89

Data Analytics Data Lake Analytics Unstructured Data 89

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. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Modeling 66

Cloudera

AUGUST 20, 2021

How CDP Enables and Accelerates Data Product Ecosystems. A multi-purpose platform focused on diverse value propositions for data products. As a result, CDP-enabled data products can meet multiple and varying functional and non-functional requirements that correspond to product attributes, each fulfilling specific customer needs.

Strategy 94

Strategy Cost-Benefit Visualization Data Warehouse 94

Cloudera

SEPTEMBER 12, 2022

It sounds straightforward: you just need data and the means to analyze it. The data is there, in spades. Data volumes have been growing for years and are predicted to reach 175 ZB by 2025. First, organizations have a tough time getting their arms around their data. Unified data fabric. Yes and no.

Unstructured Data 72

Unstructured Data Data Architecture Data Lake Snapshot 72

FineReport

DECEMBER 27, 2021

Business intelligence is the collection, storage, and analysis of data from firm activities to create a holistic perspective of a business. Enterprise BI typically functions by combining enterprise data warehouse and enterprise license to a BI platform or toolset that business users in various roles can use. Enterprise BI tools.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

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. Understanding how data becomes insights.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

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 80

Data Collection Visualization Data-driven Unstructured Data 80

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. According to Gartner, Inc.

Metadata 97

Metadata Machine Learning Unstructured Data Data Lake 97

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

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105