Smart Data Collective

FEBRUARY 14, 2023

However, it is important to understand the benefits and risks associated with cloud computing before making the commitment. However, there are some risks associated with using cloud-based software for business purposes. Firstly, there is always the risk of data breaches due to cyber-attacks or human error.

Risk 119

Risk Cost-Benefit Software Technology 119

datapine

MAY 2, 2023

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. This isn’t just valuable for the customer – it allows logistics companies to see patterns at play that can be used to optimize their delivery strategies.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

DataKitchen

MARCH 20, 2025

Every pipeline has embedded data quality tests, is version controlled, and is a sharable abstraction for the team to work within and deploy with low risk. Adding tables within an existing pipeline is manageable, posing minimal disruption.

Data Quality 164

Data Quality Testing Metrics Management 164

IBM Big Data Hub

NOVEMBER 6, 2023

It’s at these endpoints that company and user data is vulnerable to various types of attacks and security risks, including: Authentication-based attacks : where hackers try to guess or steal user passwords or exploit weak authentication processes to gain access to API servers.

Optimization 113

Optimization Testing Software Risk 113

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. Industries harness predictive analytics in different ways.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

BizAcuity

FEBRUARY 21, 2025

Marketing gaining precise insights into ROI, allowing them to optimize ad spend and refine campaign strategies With such integration, you can expect measurable improvements, as decisions are made based on a single, reliable source of truth rather than disconnected reports. Well keep you in the loop on all things data!

Dashboards 52

Dashboards Optimization Finance Sales 52

Cloudera

DECEMBER 19, 2023

There, I met with IT leaders across multiple lines of business and agencies in the US Federal government focused on optimizing the value of AI in the public sector. AI can optimize citizen-centric service delivery by predicting demand and customizing service delivery, resulting in reduced costs and improved outcomes.

Optimization 91

Optimization Cost-Benefit Unstructured Data Risk 91

IBM Big Data Hub

JANUARY 25, 2024

Many asset-intensive businesses are prioritizing inventory optimization due to the pressures of complying with growing industry 4.0 When assets lack criticality and priority assignments, there is a risk of accumulating unnecessary parts that might become obsolete on the shelves. Now, consider the just-in-case approach.

Optimization 73

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 73

Cloudera

NOVEMBER 13, 2024

AI Co-pilot: The co-pilot empowers data teams with a real-time, unified workspace that automates, optimizes, and interprets scripts while providing immediate insights into data lineage. It allows users to mitigate risks, increase efficiency, and make data strategy more actionable than ever before.

Metadata 90

Metadata Management Data Governance Data-driven 90

datapine

AUGUST 19, 2020

In our cutthroat digital economy, massive amounts of data are gathered, stored, analyzed, and optimized to deliver the best possible experience to customers and partners. At the same time, inventory metrics are needed to help managers and professionals in reaching established goals, optimizing processes, and increasing business value.

Metrics 286

Metrics KPI Cost-Benefit Dashboards 286

IBM Big Data Hub

SEPTEMBER 27, 2023

All this reduces the risk of a data leak or unauthorized access. Additionally, efficiently optimizing an open source LLM can reduce latency and increase performance. Education on these risks is one answer to these issues of data and AI. An LLM like Falcon-40B, offered under an Apache 2.0 It trained on a dataset containing 1.5

Risk 91

Risk Modeling Cost-Benefit Enterprise 91

Cloudera

DECEMBER 17, 2024

Traditional data architectures struggle to handle these workloads, and without a robust, scalable hybrid data platform, the risk of falling behind is real. High-velocity workloads like network data are best managed on-premises, where operators have more control and can optimize costs.

Enterprise 62

Enterprise Data Architecture Data-driven Optimization 62

datapine

FEBRUARY 14, 2021

That’s why it’s critical to monitor and optimize relevant supply chain metrics. While there are numerous KPI examples you can select for your assessment and optimization, we have focused on a list that will enable you to identify potential bottlenecks and ensure sustainable development. Delivery Time.

Metrics 260

Metrics KPI Dashboards Sales 260

IBM Big Data Hub

MARCH 6, 2024

The hybrid model allows organizations to gradually transition to the cloud, managing risks associated with a complete migration while benefiting from cloud scalability and flexibility. Re-platforming With a re-platforming migration, some adjustments or optimizations are made to the applications before moving them to the cloud.

Optimization 73

Optimization Strategy Cost-Benefit Testing 73

DataKitchen

NOVEMBER 5, 2024

Data is typically organized into project-specific schemas optimized for business intelligence (BI) applications, advanced analytics, and machine learning. Quality testing at every stage—Bronze, Silver, and Gold—not only helps catch issues early but also minimizes the risk of data inconsistencies surfacing in customer-facing insights.

Data Quality 198

Data Quality Testing Metrics Reporting 198

AWS Big Data

OCTOBER 11, 2024

By implementing a robust snapshot strategy, you can mitigate risks associated with data loss, streamline disaster recovery processes and maintain compliance with data management best practices. See blog post to understand how to use snapshot management policies to manage automated snapshot in OpenSearch Service.

Snapshot 111

Snapshot Dashboards Management Testing 111

CIO Business Intelligence

NOVEMBER 8, 2023

This requires knowing the risks involved with the cloud, which include external risks and threats, as well as internal risks and threats that could not only lead to a security compromise or an embarrassing leak but may affect organizations’ overall productivity and efficiency. 8 Complexity. 8 Complexity. Operational costs.

Cost-Benefit 135

Cost-Benefit Risk Digital Transformation Reporting 135

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. We’re not encouraging skepticism or fear, but companies should start AI products with a clear understanding of the risks, especially those risks that are specific to AI.

Enterprise 342

Enterprise Testing Modeling Reporting 342

datapine

OCTOBER 7, 2020

They keep your operations on schedule: While there are metrics examples that focus on strategic initiatives, as we mentioned, they will also help you in measuring day-to-day or weekly activities, which, in turn, will help you in keeping your operations on schedule and optimize them to improve results. IT: Average Handle Time.

KPI 269

KPI Metrics Sales Visualization 269

Smarten

FEBRUARY 19, 2025

Supply Chain The organization can forecast demand and manage the supply chain to optimize inventory using machine learning to predict customer demand, seasonality, product trends etc., This creates a more personalized and targeted shopping experience that is unique to each customer.

Predictive Analytics 62

Predictive Analytics Analytics Predictive Modeling Forecasting 62

CIO Business Intelligence

MAY 21, 2024

It will serve as the “nerve center” of an enterprise’s IT operation, the company said, adding that the offering will generate insights across an enterprise’s folio of applications to help reduce risk and compliance processes.

Enterprise 110

Enterprise Management Data Lake Risk 110

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in. What Are the Risks?

IT 348

IT Modeling Testing Risk 348

CIO Business Intelligence

SEPTEMBER 12, 2023

As with many disruptive innovations, Generative AI holds great promise to deliver fundamentally better outcomes for organizations, while at the same time posing an entirely new set of cybersecurity risks and challenges. Please see our Symantec Enterprise Blog and our Generative AI Protection Demo for more details.

Risk 131

Risk Enterprise Software Marketing 131

Cloudera

AUGUST 3, 2021

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Digital Transformation is not without Risk.

Analytics 111

Analytics Digital Transformation Forecasting Risk 111

CIO Business Intelligence

NOVEMBER 20, 2024

“While organizations around the world recognize the value and potential of AI, for AI to be truly effective, it must be tailored to specific industry needs,” said Satish Thomas, corporate VP of business and industry solutions at Microsoft, in a blog post.

Manufacturing 122

Manufacturing Marketing Finance Modeling 122

Cloudera

AUGUST 12, 2021

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. Risk Management. A 2019 HBR article mentioned how organizational decisions backed by data have instilled more confidence and reduced risk. Conclusion.

Data-driven 111

Data-driven Manufacturing Insurance Risk Management 111

erwin

SEPTEMBER 10, 2020

In a previous blog , I explained that data lineage is basically the history of data, including a data set’s origin, characteristics, quality and movement over time. This information is critical to regulatory compliance, change management and data governance not to mention delivering an optimal customer experience.

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

erwin

OCTOBER 8, 2020

And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. We start with an assessment of your cloud migration strategy to determine what automation and optimization opportunities exist. Subscribe to the erwin Expert Blog.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

Smart Data Collective

JULY 16, 2023

According to a report by Dataversity , a growing number of hedge funds are utilizing data analytics to optimize their rick profiles and increase their ROI. The Imperative of Risk Mitigation A crucial element in the world of financial investments is effective hedge fund management.

ROI 97

ROI Data Analytics Analytics Risk Management 97

O'Reilly on Data

MAY 14, 2020

Because they are building an AI product that will be consumed by the masses, it’s possible (perhaps even desirable) to optimize for rapid experimentation and iteration over accuracy—especially at the beginning of the product cycle. Conclusion. Nobody has all of the skills at the same time, so get to work building the ones you need.

Management 364

Management Experimentation B2B Machine Learning 364

CIO Business Intelligence

SEPTEMBER 26, 2024

Dynamics 365 Business Central is Microsoft’s flagship SMB ERP product, optimized to help businesses thrive in a new world of cloud and AI computing,” Morton said in a blog post announcing the end of support. These may go out of support as well exposing customers to a variety of security and operational risks.“

Risk 130

Risk Enterprise Strategy Software 130

IBM Big Data Hub

APRIL 12, 2024

This blog series discusses the complex tasks energy utility companies face as they shift to holistic grid asset management to manage through the energy transition. Asset investment planning (AIP) tools bring value in optimizing various, sometimes conflicting, value drivers.

Optimization 81

Optimization Risk Risk Management Management 81

Cloudera

OCTOBER 12, 2020

With the addition of Eventador we can deliver more customer value for real-time analytics use cases including: Inventory optimization, predictive maintenance and a wide variety of IoT use cases for operations teams. . Risk management and real-time fraud analysis for IT and finance teams. Stay tuned for more product updates coming soon!

IoT 132

IoT Risk Management Finance Sales 132

AWS Big Data

JULY 29, 2024

Despite their advantages, traditional data lake architectures often grapple with challenges such as understanding deviations from the most optimal state of the table over time, identifying issues in data pipelines, and monitoring a large number of tables. It is essential for optimizing read and write performance.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

CIO Business Intelligence

OCTOBER 25, 2023

Zscaler Enterprises will work to secure AI/ML applications to stay ahead of risk Our research also found that as enterprises adopt AI/ML tools, subsequent transactions undergo significant scrutiny. In all likelihood, we will see other industries take their lead to ensure that enterprises can minimize the risks associated with AI and ML tools.

Enterprise 133

Enterprise Manufacturing Risk Data-driven 133

IBM Big Data Hub

APRIL 19, 2024

This blog series discusses the complex tasks energy utility companies face as they shift to holistic grid asset management to manage through the energy transition. Asset performance management (APM) processes, such as risk-based and predictive maintenance and asset investment planning (AIP), enable health monitoring technologies.

Management 85

Management Internet of Things Risk IoT 85