CIO Business Intelligence

AUGUST 9, 2022

Data engineers and data scientists often work closely together but serve very different functions. Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data engineer vs. data architect. Becoming a data engineer.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. Data ingestion, whether real time or batch, forms the basis of any effective data analysis, enabling organizations to gather information from diverse sources and use it for insightful decision-making.

Data Warehouse 110

Data Warehouse Testing Data Quality Reporting 110

TDAN

JUNE 18, 2019

The first step to fixing any problem is to understand that problem—this is a significant point of failure when it comes to data. Most organizations agree that they have data issues, categorized as data quality. However, this definition is […].

Data Quality 90

Data Quality Data Architecture IT Data Strategy 90

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 68

Data Quality Data Integration Metadata Cost-Benefit 68

IBM Big Data Hub

FEBRUARY 9, 2023

Realize that a data governance program cannot exist on its own – it must solve business problems and deliver outcomes. Start by identifying business objectives, desired outcomes, key stakeholders, and the data needed to deliver these objectives. So where are you in your data governance journey?

Data Governance 82

Data Governance Business Objectives Strategy Data Quality 82

Cloudera

DECEMBER 28, 2017

With big data platforms, like ones based on open source software, banks can more effectively adapt to and quickly manage the wave of rules coming at them. In fact, the only thing that’s guaranteed is that the rate of regulatory change will only continue to increase over time.

Big Data 40

Big Data Data Architecture Data Quality Machine Learning 40

Octopai

APRIL 19, 2021

Her Twitter page is filled with interesting articles, webinars, reports, and current news surrounding data management. She tweets and retweets about topics such as data governance, data strategy, and data architecture. Datanami is a portal that posts about the latest news and updates when it comes to big data.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

AWS Big Data

APRIL 19, 2023

The goal of a data product is to solve the long-standing issue of data silos and data quality. Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights.

Technology 86

Technology Data-driven Machine Learning Sales 86

IBM Big Data Hub

JUNE 30, 2022

The diversity of data types, data processing, integration and consumption patterns used by organizations has grown exponentially. Extend data governance to foster trust in your data by creating transparency, eliminating bias and ensuring explainability for data and insights fueled by machine learning and AI.

Data Strategy 57

Data Strategy Strategy Business Objectives Data-driven 57

IBM Big Data Hub

JANUARY 25, 2023

Breaking down these silos to encourage data access, data sharing and collaboration will be an important challenge for organizations in the coming years. The right data architecture to link and gain insight across silos requires the communication and coordination of a strategic data governance program.

Data Governance 52

Data Governance Data-driven Strategy Management 52

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

IBM Big Data Hub

AUGUST 15, 2022

How does a data architecture impact your ability to build, scale and govern AI models? To be a responsible data scientist, there’s two key considerations when building a model pipeline: Bias: a model which makes predictions for people of different group (or race, gender ethnic group etc.)

Data mining 62

Data mining Risk Modeling Risk Management 62

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

Data Architecture 82

Data Architecture Cost-Benefit Digital Transformation Business Driver 82

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

Smart Data Collective

FEBRUARY 23, 2021

However, while doing so, you need to work with a lot of data and this could lead to some big data mistakes. But why use data-driven marketing in the first place? When you collect data about your audience and campaigns, you’ll be better placed to understand what works for them and what doesn’t. Using Small Datasets.

Big Data 116

Big Data Visualization Data Quality Data-driven 116

Peter James Thomas

AUGUST 18, 2018

Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

IBM Big Data Hub

SEPTEMBER 7, 2022

Do your data governance systems desperately need an overhaul or is your data visualization in need of a spruce up? Do you accept that data science takes a slight back seat while you improve the data quality?

Data Strategy 52

Data Strategy Strategy Data-driven Data Quality 52

TDAN

JUNE 21, 2022

Twenty-five years ago today, I published the first issue of The Data Administration Newsletter. It only took a few months to recognize that there was an audience for an “online” publication focused on data administration. […].

Publishing 78

Publishing Data Quality Data Architecture IT 78

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

IBM Big Data Hub

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. Organizations can harness the full potential of their data while reducing risk and lowering costs. However, businesses scaling AI face entry barriers.

Cost-Benefit 72

Cost-Benefit Data Integration Data Architecture Manufacturing 72

TDAN

SEPTEMBER 7, 2022

Insightful and accurate data is the lifeblood of any successful business. There are many ways to ensure high-quality information in Salesforce Sales Cloud with regular cleansing routines that keep up-to date records for each […].

Sales 52

Sales Data Quality Data Architecture IT 52

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 90

Data Lake Analytics Snapshot Optimization 90

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. Addressing the Complexities of Metadata Management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Peter James Thomas

MAY 3, 2019

Control of Data to ensure it is Fit-for-Purpose. This refers to a wide range of activities from Data Governance to Data Management to Data Quality improvement and indeed related concepts such as Master Data Management. Data Architecture / Infrastructure. Best practice has evolved in this area.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 72

Data Strategy Strategy Data Warehouse Prescriptive Analytics 72

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 88

Management Metadata Data Architecture Data Lake 88

TDAN

MAY 14, 2019

Cross-Agency Priority (CAP) Goal #2 is “leverage data as a strategic asset to grow the economy, increase the effectiveness of the Federal Government, facilitate oversight, and promote transparency.” The President’s Management Agenda (PMA) lays out a long-term vision for modernizing the Federal Government.

Management 40

Management Data Quality Data Architecture Metadata 40

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Volume.

Cost-Benefit 87

Cost-Benefit Technology Big Data Metadata 87

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Volume.

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75

IBM Big Data Hub

AUGUST 1, 2022

Bad data costs companies an average of $15 million. . 73% of business executives are unhappy with their data quality. . 61% of organizations are unable to harness data to create a sustained competitive advantage. . Thus, why we have made efforts to help companies improve their business practices through data analysis.

Unstructured Data 52

Unstructured Data Deep Learning Data Quality Data Architecture 52

IBM Big Data Hub

DECEMBER 4, 2023

During configuration, an organization constructs its data architecture and defines user roles. Specifically, to ensure the accuracy of data, organizations should test the following variables: Data archive: Make sure older data that might not have been imported to Oracle is archived securely and is easy to access.

Testing 80

Testing Consulting Digital Transformation Cost-Benefit 80

Alation

JANUARY 25, 2022

Gartner is explicit: Data catalogs play a foundational role in the data fabric. And leaders are recognizing the value of a strong data foundation. Indeed, the foundation of your data architecture and strategy – and thus your business strategy – begins with choosing the best data catalog to support your business.

Metadata 52

Metadata IT Metrics Data-driven 52

IBM Big Data Hub

JANUARY 17, 2023

As part of a data fabric, IBM’s data integration capability creates a roadmap that helps organizations connect data from disparate data sources, build data pipelines, remediate data issues, enrich data quality, and deliver integrated data to multicloud platforms.

Data-driven 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

Peter James Thomas

AUGUST 2, 2019

Data Architecture – Definition (2). Data Catalogue. Data Community. Data Domain (contributor: Taru Väre ). Data Enrichment. Data Federation. Data Function. Data Model. Data Operating Model. Thanks to all of these for their help. Application Programming Interface (API).

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This results in more marketable AI-driven products and greater accountability.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64