Octopai

DECEMBER 22, 2019

As 2019 comes to a close, we think it’s the perfect time to review trends in metadata management as well as look at some of Octopai’s own highlights. What a flashback to see all that we’ve achieved this year in data governance, risk and compliance, data analysis and reporting. View more news from 2019 and beyond here.

Metadata 54

Metadata Management OLAP Data Governance 54

Alation

APRIL 25, 2023

That means if you haven’t already incorporated a plan for data governance into your long-term vision for your business, the time is now. Let’s take a closer look at what data governance is — and the top five mistakes to avoid when implementing it. 5 common data governance mistakes 1.

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Data Governance Marketing Machine Learning Sales 40

Alation

MAY 19, 2022

Establish what data you have. Active metadata gives you crucial context around what data you have and how to use it wisely. Active metadata provides the who, what, where, and when of a given asset, showing you where it flows through your pipeline, how that data is used, and who uses it most often. Data Governance.

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Octopai

SEPTEMBER 22, 2019

. – Property insurers are using troves of geographical, geological, climate, and other data to assess all kinds of hazard risks. – All types of insurance companies are leveraging data analytics to detect and prosecute fraud. Insurance Metadata Management. Both of these two keys deal with metadata.

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Cloudera

APRIL 18, 2024

More Businesses Are Taking a Holistic Approach to Data Strategy One of the more common trends we saw coming up through conversations during the summit was the need for a reframing of how we approach data strategy—taking a much more holistic viewpoint to it than organizations otherwise would have in past years.

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DataKitchen

JANUARY 5, 2021

The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance.

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Alation

AUGUST 30, 2022

We continue to make deep investments in governance, including new capabilities in the Stewardship Workbench, a core part of the Data Governance App. Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. Then Alation came along.

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Metadata Data Quality Data Governance Machine Learning 52

CIO Business Intelligence

MARCH 4, 2024

The human political element plays a significant role here as well, as local data owners push back on relinquishing control over domain-specific data assets to centralized data governance authorities. These domain data leaders often cite the diminishing returns and significant effort of central data team engagement.

Insurance 86

Insurance Strategy Data Governance Data Integration 86

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? I saw the winds change and the inquiry requests shifted towards advanced analytics involving machine learning (ML) questions. Then in the middle of 2017, a realization set in that we were one year away from GDPR and needed to focus on data governance.

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Alation

FEBRUARY 13, 2020

By leveraging Google-like smart search to find data assets; using automation and self-learning instead of burdening people with the need to manually update metadata in multiple places; and ensuring that metadata is maintained by the whole data community and is not dependent on a centralized IT team.

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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.

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Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

JUNE 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Why you should automate data governance and how a data fabric architecture helps.

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Andrew White

DECEMBER 9, 2019

The outline of the call went as follows: I was taking to a central state agency who was organizing a data governance initiative (in their words) across three other state agencies. All four agencies had reported an independent but identical experience with data governance in the past. Information (processed data).

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erwin

OCTOBER 16, 2020

And this time sensitivity is a massive issue, as taking a proactive and data-driven approach can literally mean life or death to your business or to your customers. And that’s where data analytics can play a huge role. 1 of erwin Insights 2020, our virtual conference on enterprise modeling and data governance/intelligence.

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IBM Big Data Hub

JANUARY 5, 2023

Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.

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Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

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erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Data Governance Bottlenecks. Regulations.

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Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. But it’s still not easy.

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Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. SECURITY AND GOVERNANCE LEADERSHIP. Winners included: Connect the Data Lifecycle: Globe Telecom — Raising experience standards and helping customers live enhanced mobile lifestyles.

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CIO Business Intelligence

MARCH 29, 2022

. • You have data but don’t use it. Why does valuable data so often go unused? Lack of annotation with the right metadata is a contributing factor. An even larger issue is that people may not know how to see value in data. Recognizing what data can tell you is an acquired skill for people beyond just data scientists.

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AWS Big Data

OCTOBER 4, 2023

Collaboration – Analysts, data scientists, and data engineers often own different steps within the end-to-end analytics journey but do not have an simple way to collaborate on the same governed data, using the tools of their choice.

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Metadata Data Lake Publishing Data Governance 98

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. What are common data challenges for the travel industry? Travel can be stressful and emotionally fraught.

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DataKitchen

FEBRUARY 2, 2023

A combined, interoperable suite of tools for data team productivity, governance, and security for large and small data teams. And the tools for acting on data are consolidating: Tableau does data prep, Altreyx does data science, Qlik joined with Talend, etc. And their business customers want more data trust.

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TDAN

APRIL 6, 2021

There is an ever-increasing awareness of concerns about data privacy, corporate data breaches, increasing demands for regulatory compliance. There are also emerging concerns about the ways that big data analytics potentially influence and bias automated decision-making.

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IBM Big Data Hub

JANUARY 17, 2023

Essential components of a data lakehouse architecture and what makes an open data lakehouse. At the core of a data lakehouse architecture includes the storage, metadata service and the query engine, and typically a data governance component made up of a policy engine and a data dictionary.

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Data Lake Metadata Data Warehouse Data Governance 52

TDAN

NOVEMBER 3, 2020

In the September issue of TDAN.com, Anthony Algmin denounced Data Catalogs as a “1980’s solution to a 2020’s problem.” What is the state of data science today? As I state in my book, The Data Catalog: Sherlock Holmes Sleuthing for Data Analytics and in many articles, 80% (or more) of a data analyst’s […].

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AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. This solution only replicates metadata in the Data Catalog, not the actual underlying data.

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Data Architecture Metadata Data Lake Snapshot 65

Alation

APRIL 14, 2022

This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. The Cloud Data Migration Challenge. Data Governance and Data Security.

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Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. 2 “Exposing The Data Mesh Blind Side ” Forrester.

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Management Metadata Data Architecture Data Lake 83

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) And that makes sense.

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Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

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Metadata Data-driven Insurance Statistics 52

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Then, you transform this data into a concise format.

Data Strategy 67

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IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance.

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AWS Big Data

JUNE 9, 2023

Data in customers’ data lakes is used to fulfil a multitude of use cases, from real-time fraud detection for financial services companies, inventory and real-time marketing campaigns for retailers, or flight and hotel room availability for the hospitality industry.

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Data Lake Metadata Optimization Statistics 111

AWS Big Data

JANUARY 22, 2024

Discussions with users showed they were happier to have faster access to data in a simpler way, a more structured data organization, and a clear mapping of who the producer is. A lot of progress has been made to advance their data-driven culture (data literacy, data sharing, and collaboration across business units).

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IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape.

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Domino Data Lab

AUGUST 8, 2019

In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. First and foremost: there’s substantial overlap between what the scientific community is working toward for scholarly infrastructure and some of the current needs of data governance in industry. We did it again.”.

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Data Science Machine Learning Data Governance Statistics 71