Jet Global

SEPTEMBER 4, 2020

There is an established body of practice around creating, managing, and accessing OLAP data (known as “cubes”). Data Lakes. There has been a lot of talk over the past year or two in the D365F&SCM world about “data lakes.” Traditional databases and data warehouses do not lend themselves to that task.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conceivable business function.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. With a cloud deployment, enterprises can leverage a “pay as you go” model; reducing the burden of incurring capital costs. Data that needs to be tightly controlled (e.g. AWS Propelling Hybrid Cloud Environments.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

CIO Business Intelligence

SEPTEMBER 21, 2023

Generative AI touches every aspect of the enterprise, and every aspect of society,” says Bret Greenstein, partner and leader of the gen AI go-to-market strategy at PricewaterhouseCoopers. If you take something slightly risky and make it a thousand times bigger, the risks are amplified,” he says. But it’s a sign of what’s to come. “If

Enterprise 128

Enterprise Consulting Modeling Cost-Benefit 128

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 73

Risk Modeling Management Metadata 73

IBM Big Data Hub

MAY 9, 2023

We can use foundation models to quickly perform tasks with limited annotated data and minimal effort; in some cases, we need only to describe the task at hand to coax the model into solving it. But these powerful technologies also introduce new risks and challenges for enterprises.

Enterprise 131

Enterprise Technology Modeling Cost-Benefit 131

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. Data Modeling.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

CIO Business Intelligence

SEPTEMBER 20, 2023

The data can also help us enrich our commodity products. How are you populating your data lake? We’ve decided to take a practical approach, led by Kyle Benning, who runs our data function. Then our analytics team, an IT group, makes sure we build the data lake in the right sequence.

Data Lake 124

Data Lake Data-driven Dashboards Risk 124

Octopai

JUNE 30, 2022

Establishing a single, enterprise-wide source of truth? Increasing data quality and accuracy? Why are data catalog use cases so downright… predictable? If you can rattle off the top five or ten enterprise data catalog use cases in your sleep, this post is an attempt to add a little more color and variety to your data life.

Enterprise 72

Enterprise Data-driven Data Lake Data Quality 72

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. The continued federation of data in the enterprise resulted in data silos.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

CIO Business Intelligence

APRIL 1, 2024

Deloitte 2 meanwhile found that 41% of business and technology leaders said a lack of talent, governance, and risks are barriers to broader GenAI adoption. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Low-cost proof-of-concepts can help you reduce the risk of overprovisioning.

Data Lake 130

Data Lake Consulting Uncertainty Risk 130

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 102

Data Lake Data Warehouse Management Risk 102

Alation

FEBRUARY 13, 2020

We also have some primary insurance entities in the group, but the main thing about reinsurance is that we’re taking care of the big and complex risks in the world. A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives.

Data-driven 52

Data-driven Data Lake Enterprise Analytics 52

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 97

Data Governance Unstructured Data Metadata Data Lake 97

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 57

Data-driven Enterprise Data Governance Data Lake 57

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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 107

Data Lake Unstructured Data Data Warehouse Data Quality 107

AWS Big Data

FEBRUARY 27, 2023

Data sharing is becoming an important element of an enterprise data strategy. AWS services like AWS Data Exchange provide an avenue for companies to share or monetize their value-added data with other companies.

Enterprise 87

Enterprise Publishing Data Lake Management 87

Alation

FEBRUARY 20, 2020

Imagine a new type of business, one in which the fabric of data is so woven throughout the enterprise that it becomes almost a living, breathing entity that one day may even be able to make the right decisions for you. This enables them to experiment with building model behaviors to drive more accurate insurance risk analysis.

Enterprise 52

Enterprise Data Processing Data Lake Insurance 52

AWS Big Data

MAY 30, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Data Warehouse 85

Data Warehouse Data Lake Cost-Benefit Structured Data 85

AWS Big Data

MARCH 27, 2023

Data lakes have come a long way, and there’s been tremendous innovation in this space. Today’s modern data lakes are cloud native, work with multiple data types, and make this data easily available to diverse stakeholders across the business. In the navigation pane, under Data catalog , choose Settings.

Data Lake 88

Data Lake Data-driven Management Data Architecture 88

Alation

FEBRUARY 13, 2020

Following a very successful year of growth in Alation’s business, this announcement marks a milestone for Alation and the enterprise data catalog market. What started six years ago as one startup trying to improve the way people work with data has become a full-blown market category – Machine Learning Data Catalogs.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 103

Data Warehouse Data Lake Analytics Machine Learning 103

CIO Business Intelligence

JANUARY 20, 2023

Doing it right requires thoughtful data collection, careful selection of a data platform that allows holistic and secure access to the data, and training and empowering employees to have a data-first mindset. Security and compliance risks also loom. Most organizations don’t end up with data lakes, says Orlandini.

Data Lake 130

Data Lake Data-driven Finance Data Architecture 130

Cloudera

AUGUST 13, 2021

Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis.

Analytics 109

Analytics Data Lake Unstructured Data Enterprise 109

erwin

OCTOBER 31, 2019

Data security incidents may be the result of not having a true data governance foundation that makes it possible to understand the context of data – what assets exist and where, the relationship between them and enterprise systems and processes, and how and by what authorized parties data is used. No Hocus Pocus.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

OCTOBER 18, 2023

But if there are any stop signs ahead regarding risks and regulations around generative AI, most enterprise CIOs are blowing past them, with plans to deploy an abundance of gen AI applications within the next two years if not already. for internal enterprise exploration. First, we launched a private instance of GPT-3.5

Risk 138

Risk Manufacturing Enterprise Technology 138

CIO Business Intelligence

AUGUST 3, 2023

And at First Commerce Bank, EVP and COO Gregory Garcia hopes to leverage unified, real-time data to monitor risks such as worsening vacancy rates that could make it harder for commercial property owners to pay their mortgages. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 95

Analytics Data Lake Metadata Cost-Benefit 95

Cloudera

JANUARY 30, 2023

And this doesn’t even touch on the data generated by citizen services interfaces, machine or device-generated data such as video feeds, sensors, and communications data. This dark data resides everywhere in the enterprise, siloed in multiple data repositories, from laptops and mobile devices to data lakes and applications.

IoT 82

IoT Data Architecture Data Lake Machine Learning 82

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

CIO Business Intelligence

OCTOBER 19, 2022

The CIO’s evolving data role Data falls into a similar category as digital. CIOs are responsible for building an enterprise data and analytics capability, but they do not own data as a function. If that is the case, where should the data and analytics function sit? What about risk?

IT 119

IT Digital Transformation Data Warehouse Risk 119

Cloudera

DECEMBER 14, 2022

OCBC Bank optimizes customer experience & risk management with multi-phased data initiative. The company recently migrated to Cloudera Data Platform (CDP ) and CDP Machine Learning to power a number of solutions that have increased operational efficiency, enabled new revenue streams and improved risk management.

Data Strategy 79

Data Strategy Strategy IT Contextual Data 79

DataKitchen

JULY 27, 2023

It provides data prep, management, and enterprise data warehousing tools. It has a data pipeline tool , as well. Azure Logic Apps: This service helps you schedule, automate, and orchestrate tasks, business processes, and workflows when integrating apps, data, systems, and services across enterprises or organizations.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Lack of a solid data governance foundation increases the risk of data-security incidents.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Alation

JUNE 17, 2021

“Data governance is critical to Snowflake customers and Alation drives data governance across the enterprise,” said Colleen Kapase, SVP of Worldwide Partner and Alliances at Snowflake. Alation combines governance and data democratization capabilities into one unified solution and is a foundational part of the Snowflake platform.

Data Governance 98

Data Governance Data Lake Insurance Enterprise 98