David Menninger's Analyst Perspectives

MARCH 30, 2020

I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.

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CIO Business Intelligence

JULY 23, 2023

More than 60% of corporate data is unstructured, according to AIIM , and a significant amount of this unstructured data is in the form of non-traditional “records,” like text and social media messages, audio files, video, and images. Data Management

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O'Reilly on Data

FEBRUARY 11, 2020

They have too many different data sources and too much inconsistent data. They don’t have the resources they need to clean up data quality problems. The building blocks of data governance are often lacking within organizations. Nearly one-quarter of respondents work as data scientists or analysts (see Figure 1).

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CIO Business Intelligence

DECEMBER 5, 2024

Instead of overhauling entire systems, insurers can assess their API infrastructure to ensure efficient data flow, identify critical data types, and define clear schemas for structured and unstructured data. Incorporating custom knowledge graphs, enriched with domain expertise, further optimizes data consolidation.

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Rocket-Powered Data Science

MARCH 20, 2023

Datasphere accesses and integrates both SAP and non-SAP data sources into end-users’ data flows, including on-prem data warehouses, cloud data warehouses and lakehouses, relational databases, virtual data products, in-memory data, and applications that generate data (such as external API data loads).

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CIO Business Intelligence

JANUARY 24, 2024

“Similar to disaster recovery, business continuity, and information security, data strategy needs to be well thought out and defined to inform the rest, while providing a foundation from which to build a strong business.” Overlooking these data resources is a big mistake. What are the goals for leveraging unstructured data?”

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DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . DVC — Open-source Version Control System for Machine Learning Projects … data version control. Process Analytics.

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Octopai

JUNE 24, 2019

There are a number of scenarios that necessitate data governance tools. Businesses operating within strict industry regulations, utilizing analytics software, and/or regularly consolidating data in key subject areas will find themselves looking into data governance tools to help them achieve their goals.

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CIO Business Intelligence

OCTOBER 2, 2024

Collect, filter, and categorize data The first is a series of processes — collecting, filtering, and categorizing data — that may take several months for KM or RAG models. Structured data is relatively easy, but the unstructured data, while much more difficult to categorize, is the most valuable.

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CIO Business Intelligence

DECEMBER 19, 2023

Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities. But 99% also report technical challenges, listing integration (68%), data volume and cleansing (59%), and managing unstructured data (55% ) as the top three.

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erwin

JANUARY 17, 2020

In the modern context, data modeling is a function of data governance. While data modeling has always been the best way to understand complex data sources and automate design standards, modern data modeling goes well beyond these domains to accelerate and ensure the overall success of data governance in any organization.

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CIO Business Intelligence

NOVEMBER 21, 2022

In our most recent Rocket survey, 46% of IT professionals indicate that at least half of their content is “dark data”— meaning it’s processed but never used. A big reason for the proliferation of dark data is the amount of unstructured data within business operations.

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Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? 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.

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CIO Business Intelligence

OCTOBER 2, 2024

But the most advanced data and analytics platforms should be able to: a) ingest risk assessment data from a multitude of sources; b) allow analytics teams in and outside an organization to permissibly collaborate on aggregate insights without accessing raw data; and c) provide a robust data governance structure to ensure compliance and auditability.

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CIO Business Intelligence

MARCH 6, 2024

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments. “We

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CIO Business Intelligence

AUGUST 1, 2023

But with all the excitement and hype, it’s easy for employees to invest time in AI tools that compromise confidential data or for managers to select shadow AI tools that haven’t been through security, data governance, and other vendor compliance reviews.

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Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. Data governance requires a system.

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CIO Business Intelligence

JUNE 19, 2023

Achieving this requires a comprehensive upgrade across five dimensions of data intelligence — data architecture, data governance, data consumption, data security, and data talent. Mr. Cao noted the specific problem of unstructured data. “A Huawei’s new Data Intelligence Solution 3.0

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CIO Business Intelligence

JUNE 15, 2023

Achieving this requires a comprehensive upgrade across five dimensions of data intelligence — data architecture, data governance, data consumption, data security, and data talent. Mr. Cao noted the specific problem of unstructured data. “A Huawei’s new Data Intelligence Solution 3.0

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CIO Business Intelligence

AUGUST 9, 2024

According to Pruitt, one major benefit of partnering with a cloud-agnostic data giant such as Databricks and developing a sophisticated data governance strategy is “just being able to have a single source of truth.”

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Alation

SEPTEMBER 9, 2021

Internal and external auditors work with many different systems to ensure this data is protected accordingly. This is where data governance comes in: A robust program allows banks and financial institutions to use this data to build customer trust and still meet compliance mandates. What is Data Governance in Banking?

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Cloudera

OCTOBER 26, 2020

Not a day goes by without virtual conversations, creating masses of unstructured data. To be able to capitalize on this data storm, organizations must find a better balance between the security and usability related to data access. Getting to value means delivering it to those who can make sense of it: the end-users.

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CIO Business Intelligence

FEBRUARY 16, 2023

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

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Cloudera

MAY 14, 2024

This form of hybrid also goes a level deeper than one may find in a standard hybrid cloud, accounting for the entirety of the data lifecycle, whether that’s the point of ingestion, warehousing, or machine learning—even when that end-to-end data lifecycle is split between entirely different environments. Data comes in many forms.

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CIO Business Intelligence

SEPTEMBER 12, 2024

It’s critical to take a unified approach that covers both structured and unstructured data. Based on what we see with our customers, only about 20% of the data you require for any use case is typically visible, while another 20% is what we call ROT: redundant, obsolete or trivial.

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CIO Business Intelligence

OCTOBER 23, 2023

While such tools remain critical for corporations, they’re also relatively flat and robotic compared to GenAI technologies, whose sweet spot is understanding natural language prompts to generate contextually relevant information from unstructured data. It’s AI democratized for the masses.

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BI-Survey

MARCH 19, 2025

Steering Through the AI Regulatory Storm With regulations like the EU AI Act looming on the horizon, robust AI governance isn’t just good practiceit’s becoming a legal requirement. Taking Action: Your Next Steps Ready to leverage these trends in your organization? Identify specific use cases where AI could deliver immediate value.

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CIO Business Intelligence

AUGUST 9, 2023

Unstructured data needs for generative AI Generative AI architecture and storage solutions are a textbook case of “what got you here won’t get you there.” To better understand the scale of data changes, the graphic below shows the relative magnitude of generative AI data management needs, impacting both compute and storage needs.

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CIO Business Intelligence

JANUARY 22, 2024

Payers and providers will need to create a data foundation that addresses elements such as bringing in the right data, how to classify it, and how to create a data lineage so data sources can be tracked to address potential AI hallucinations. The need for generative AI data management may seem daunting.

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CIO Business Intelligence

SEPTEMBER 11, 2024

A 2024 survey by Monte Carlo and Wakefield Research found that 100% of data leaders feel pressured to move forward with AI implementations even though two out of three doubt their data is AI-ready. Those organizations are sailing into the AI storm without a proper compass – a solid enterprise-wide data governance strategy.

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CIO Business Intelligence

APRIL 19, 2023

Using technologies that support a hybrid environment makes it easier to modernize with less disruption, improving workloads, keeping data accessible and ultimately driving greater revenue. Enterprises store a vast amount of data. The less visibility and awareness IT has over data, the greater the chance that it will be exposed.

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CIO Business Intelligence

JULY 22, 2024

When you’re taking the whole of Dow’s 127 years of knowledge in the form of structured and unstructured data and putting it in a place that’s supposed to make it easier to access and find, that can be scary,” Schroeder says. There are data privacy laws, and security regulations and controls that have to be put in place.

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erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). This also diminishes the value of data as an asset.

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Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. Alation blog from Jason Lim – [link] Subscribe to Alation's Blog Get the latest data cataloging news and trends in your inbox.

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Cloudera

JANUARY 28, 2022

Then there are the more extensive discussions – scrutiny of the overarching, data strategy questions related to privacy, security, data governance /access and regulatory oversight. These are not straightforward decisions, especially when data breaches always hit the top of the news headlines.

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CIO Business Intelligence

OCTOBER 13, 2023

Application data architect: The application data architect designs and implements data models for specific software applications. Information/data governance architect: These individuals establish and enforce data governance policies and procedures.

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Cloudera

OCTOBER 5, 2023

Your organization is not alone — many organizations struggle to move towards data as the cornerstone of their organization. Here are five challenges that you need to overcome to become a data leader: Bad data governance Your insights are only as good as your data.

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