FineReport

APRIL 26, 2023

In this article, we will explore the importance of Big Data, why enterprises need Big Data tools, how to choose the right Big Data analytics tools and provide a list of the top 10 Big Data analytics tools available today. What is Big Data? What is Big Data?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

CIO Business Intelligence

JUNE 7, 2022

But only in recent years, with the growth of the web, cloud computing, hyperscale data centers, machine learning, neural networks, deep learning, and powerful servers with blazing fast processors, has it been possible for NLP algorithms to thrive in business environments. Intel® Technologies Move Analytics Forward. Putting NLP to Work.

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

Ontotext

MARCH 20, 2024

Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Studies reveal that businesses lose significant time and opportunities due to missing integrations and poor data quality and accessibility. It’s a huge productivity loss.”

Data-driven 52

Data-driven Strategy Sales Data Integration 52

CIO Business Intelligence

NOVEMBER 28, 2023

Making the most of enterprise data is a top concern for IT leaders today. With organizations seeking to become more data-driven with business decisions, IT leaders must devise data strategies gear toward creating value from data no matter where — or in what form — it resides.

Unstructured Data 129

Unstructured Data Data-driven Visualization Data Quality 129

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

CIO Business Intelligence

AUGUST 9, 2022

Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer vs. data architect.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

Ontotext

JANUARY 29, 2024

Addressing challenges such as data quality and ensuring unified, semantically consistent access to accurate, trustworthy data will require setting a clear data strategy as well as taking a realistic, business-driven approach. Sometimes, the challenge is that the data itself often raises more questions than it answers.

Strategy 52

Strategy Management Metadata Data-driven 52

CIO Business Intelligence

MARCH 29, 2022

The same principle applies to getting value from data. Organizations may acquire a lot of data, but they aren’t getting much value from it. It is estimated that nearly 75% of the data that enterprises collect remains unused, and thus, the value is not realized. What is data waste, and why does it happen?

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

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 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? Why is data analytics important for travel organizations?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

Testing 300

Testing Machine Learning Consulting Data Quality 300

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

Smart Data Collective

SEPTEMBER 26, 2021

Data mining and knowledge go hand in hand, providing insightful information to create applications that can make predictions, identify patterns, and, last but not least, facilitate decision-making. Working with massive structured and unstructured data sets can turn out to be complicated. If it’s not done right away, then later.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

IBM Big Data Hub

JANUARY 17, 2023

Technical Metadata storage/service: This component is required to understand what data is available in the storage layer. The query engine needs the metadata for the unstructured data and tables to understand where the data is located, what it looks like, and how to read it. A word on managed services.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. Why did Orca choose Apache Iceberg?

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

Grooper

AUGUST 19, 2019

Fear of disruption and growing digital transformation initiatives have created a demand for business-driven analytics. Traditional data sources like end of month statements and quarterly reports are no longer enough. They're the insights needed for better decision making, and they start with the business, not with the data.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

datapine

FEBRUARY 22, 2022

Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on. Unfortunately, this approach could be disastrous. Investing in BI shouldn’t be taken lately.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

CIO Business Intelligence

JANUARY 20, 2023

It’s About the Data For companies that have succeeded in an AI and analytics deployment, data availability is a key performance indicator, according to a Harvard Business Review report. [3] Dealing with data is where core technologies and hardware prove essential. Just starting out with analytics?

Analytics 136

Analytics Key Performance Indicator Unstructured Data IoT 136

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? However, “big data didn’t magically fix bad data,” Gildersleeve laments. “It

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

CDW Research Hub

SEPTEMBER 15, 2020

Data is a valuable asset that can help businesses reduce costs, make informed decisions, and better understand what their customers need. However, data can easily become useless if it is trapped in an outdated technology. Another critical step is to create a framework to integrate your data. Build a Best of Breed Data Platform.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

IBM Big Data Hub

AUGUST 4, 2023

Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Cloudera

APRIL 1, 2024

This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics.

Unstructured Data 106

Unstructured Data Cost-Benefit Metadata Machine Learning 106

datapine

DECEMBER 4, 2019

We mentioned predictive analytics in our business intelligence trends article and we will stress it here as well since we find it extremely important for 2020. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. in the last 5 years.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

Alation

NOVEMBER 22, 2022

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. Standardizing data formats. Scattered Data.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 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. 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