CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Preserve/Dispose.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

IBM Big Data Hub

JULY 26, 2023

AI solutions work by collecting asset performance data and feeding it into machine learning models, which can predict asset health and risk of failure. This use case shows how AI can help by processing unstructured image and video data in addition to structured data in the previous examples.

Optimization 82

Optimization Manufacturing Cost-Benefit Reporting 82

IBM Big Data Hub

APRIL 9, 2024

Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. “Being able to organize the data around that structure helps us to efficiently query, retrieve and use the information downstream, for example for AI narration.”

Management 89

Management IT Machine Learning Metrics 89

Octopai

JUNE 26, 2020

Without metadata, the organization is at risk of making decisions based on the wrong data.”. Having a metadata management system in place can greatly streamline and enhance the collection, integration and analysis processes across multiple data sources. Automated metadata governance.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

IBM Big Data Hub

AUGUST 28, 2023

Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data. Crisis management and risk management: Text mining serves as an invaluable tool for identifying potential crises and managing risks.

Data mining 60

Data mining Machine Learning Deep Learning Marketing 60

Sisense

JUNE 8, 2020

In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data. Deeper insights from bigger data sets.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

Smart Data Collective

FEBRUARY 3, 2021

Big data is changing the nature of the financial industry in countless ways. The market for data analytics in the banking industry alone is expected to be worth $5.4 However, the impact of big data on the stock market is likely to be even greater. What Impact Is Big Data Having Towards Investing?

Big Data 139

Big Data Marketing Data Analytics Analytics 139

datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

BizAcuity

MARCH 1, 2019

Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. IoT produces a treasure trove of big data.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

JULY 19, 2023

Supply Chain: Demand forecasting, supply chain optimization, risk assessment and mitigation. Robustness : AI systems should be able to withstand attacks to the training data. We started with prepping the proprietary structured data to clean and make it ready in a format to be able to pass within prompts for fine-tuning and inferencing.

Consulting 66

Consulting Machine Learning Manufacturing Optimization 66

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge. What is Big Data Fabric?

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Peter James Thomas

AUGUST 29, 2018

However, in reality, the CDO role encompasses Enterprise Data Management, although generally speaking the EDM role includes responsibility for the day to day operations of the collection processes, which in my current role I don’t have. However, it is hard to ignore the impact that Big Data and related technologies have had.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

MAY 24, 2022

Organisations are increasingly migrating their data to public cloud services to underpin their enterprise data platform. Unless properly executed such a migration can result in spiralling cloud charges, unexpected security and governance risks, and performance issues. THE CLOUDERA DATA PLATFORM & CDP PUBLIC CLOUD.

Enterprise 98

Enterprise Cost-Benefit Structured Data Data-driven 98

CIO Business Intelligence

MARCH 9, 2022

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. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Rocket-Powered Data Science

JULY 14, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Analytics 165

Analytics Internet of Things Prescriptive Analytics Data Science 165

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. The Data Catalog objects are listed under the awsdatacatalog database. FHIR data stored in AWS HealthLake is highly nested.

Data Analytics 94

Data Analytics Analytics Data Warehouse Data Lake 94

AWS Big Data

JANUARY 22, 2024

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. For Acast’s use case, granular row- or column-level access controls weren’t needed, so the approach sufficed.

Data-driven 88

Data-driven Advertising Metadata Data Architecture 88

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Metadata 87

Metadata Big Data Optimization Unstructured Data 87

Cloudera

SEPTEMBER 6, 2018

Handle increases in data volume gracefully. Represent entity relationships, to help determine ultimate beneficial owner, contribute to risk scoring, and facilitate investigations. Provide audit and data lineage information to facilitate regulatory reviews. Entity Resolution and Data Enrichment. Entity Risk Scoring.

Machine Learning 40

Machine Learning Risk Big Data Unstructured Data 40

IBM Big Data Hub

JANUARY 10, 2024

AI development and deployment can come with data privacy concerns, job displacements and cybersecurity risks, not to mention the massive technical undertaking of ensuring AI systems behave as intended. In order to “teach” a program new information, the programmer must manually add new data or adjust processes.

Unstructured Data 85

Unstructured Data Deep Learning Cost-Benefit Modeling 85

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. With erwin, organizations can: 1.

Metadata 104

Metadata Management Data-driven Data Architecture 104

IBM Big Data Hub

JULY 6, 2023

You’ll also need to create a hybrid, AI-ready architecture that can successfully use data wherever it lives—on mainframes, data centers, in private and public clouds and at the edge. Your AI must be trustworthy because anything less means risking damage to a company’s reputation and bringing regulatory fines.

Deep Learning 64

Deep Learning Machine Learning Unstructured Data Modeling 64

AWS Big Data

MARCH 26, 2024

Enrichment typically involves adding demographic, behavioral, and geolocation data. You can use third-party data products from AWS Marketplace delivered through AWS Data Exchange to gain insights on income, consumption patterns, credit risk scores, and many more dimensions to further refine the customer experience.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

JULY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data. Ensuring the complete removal of data from all these copies and backups can be challenging.

Snapshot 84

Snapshot Metadata Measurement Data Warehouse 84

Sisense

JUNE 5, 2019

We live in an era of Big Data. The sheer volume of data currently existing is huge enough without also grappling with the amount of new information that’s generated every day. It’s no wonder, then, that NoSQL databases are seeing a lot of use in Big Data and real-time web apps. Cloud Solutions. Decision Time.

Big Data 75

Big Data Cost-Benefit IoT Structured Data 75

Cloudera

OCTOBER 3, 2018

In 2008, I co-founded Cloudera with folks from Google, Facebook, and Yahoo to deliver a big data platform built on Hadoop to the enterprise market. We believed then, and we still believe today, that the rest of the world would need to capture, store, manage and analyze data at massive scale. Forward-Looking Statements.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

AWS Big Data

APRIL 19, 2023

Different departments within an organization can place data in a data lake or within their data warehouse depending on the type of data and usage patterns of that department. If not done right, you can end up with data latency issues, inaccuracies, and potential security and data governance risks.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

Domino Data Lab

MARCH 3, 2019

Over the past six months, Ben Lorica and I have conducted three surveys about “ABC” (AI, Big Data, Cloud) adoption in enterprise. There are essentially four types encountered: image/video, audio, text, and structured data.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

erwin

AUGUST 31, 2023

Let’s explore the continued relevance of data modeling and its journey through history, challenges faced, adaptations made, and its pivotal role in the new age of data platforms, AI, and democratized data access. Relational databases adapt to handle web-scale data.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

IBM Big Data Hub

AUGUST 15, 2023

To that end, IBM is building a set of domain-specific foundation models that go beyond natural language learning models and are trained on multiple types of business data, including code, time-series data, tabular data, geospatial data, semi-structured data, and mixed-modality data such as text combined with images.

IT 84

IT Data Governance Modeling Cost-Benefit 84

Sisense

JULY 23, 2021

Not only does it support the successful planning and delivery of each edition of the Games, but it also helps each successive OCOG to develop its own vision, to understand how a host city and its citizens can benefit from the long-lasting impact and legacy of the Games, and to manage the opportunities and risks created.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

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 103

Unstructured Data Cost-Benefit Metadata Machine Learning 103

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. smava was looking for an out-of-the-box solution to achieve workload isolation without managing a complex data replication pipeline.

Data Lake 92

Data Lake Data Warehouse Data-driven B2B 92

Jet Global

MAY 9, 2024

The architecture may vary depending on the specific use case and requirements, but it typically includes stages of data ingestion, transformation, and storage. Data ingestion methods can include batch ingestion (collecting data at scheduled intervals) or real-time streaming data ingestion (collecting data continuously as it is generated).

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52