AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. Flat files – Other systems supply data in the form of flat files of different formats. Data ingestion Data from various sources are grouped into two major categories: real-time ingestion and batch ingestion.

Data Warehouse 109

Data Warehouse Testing Data Quality Reporting 109

Anmut

APRIL 6, 2023

By regularly conducting data maturity assessments, you can catch potential issues early and make proactive changes to supercharge your business’s success. Improved data quality By assessing the organisation’s data quality management practices, the assessment can identify areas where data quality can be improved.

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 52

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

Ontotext

APRIL 10, 2024

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Cloudera

MARCH 28, 2024

But, even with the backdrop of an AI-dominated future, many organizations still find themselves struggling with everything from managing data volumes and complexity to security concerns to rapidly proliferating data silos and governance challenges. The benefits are clear, and there’s plenty of potential that comes with AI adoption.

Data Architecture 88

Data Architecture Strategy Data Lake Data-driven 88

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., Click here to get a free copy of the report. by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer vs. data architect.

Analytics 130

Analytics Data Science Statistics Unstructured Data 130

erwin

SEPTEMBER 17, 2020

According to erwin’s “2020 State of Data Governance and Automation” report , close to 70 percent of data professional respondents say they spend an average of 10 or more hours per week on data-related activities, and most of that time is spent searching for and preparing data.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

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 79

Data Governance Business Objectives Strategy Data Quality 79

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., Click here to get a free copy of the report. by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Octopai

APRIL 19, 2021

Without organized metadata management, the validity of a company’s data is compromised and they won’t achieve adequate compliance, data governance, or generate correct insights. Additionally, the BI team will have trouble pinpointing the cause of errors, leading to inaccurate reports. TDWI – David Loshin.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

Jedox

OCTOBER 22, 2020

Other challenges to data analytics include data storage, data quality, and a lack of knowledge and tools necessary to make sense of the data and generate those critical insights. Limited self-service reporting across the enterprise. Self-service reporting. Exception reporting.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 82

Data Architecture Risk Management Risk Management 82

CIO Business Intelligence

APRIL 29, 2022

The data-first transformation journey can appear to be a lengthy one, but it’s possible to break it down into steps that are easier to digest and can help speed you along the pathway to achieving a modern, data-first organization. Key features of data-first leaders. 5x more likely to be highly resilient in terms of data loss.

Digital Transformation 128

Digital Transformation Strategy Data-driven Data Strategy 128

CIO Business Intelligence

JANUARY 30, 2024

Corporate ESG reporting is getting real for companies around the globe. Enacted and proposed regulations in the EU, US, and beyond are deepening reporting requirements in an effort to change business behavior. The foundation for ESG reporting, of course, is data. The foundation for ESG reporting, of course, is data.

Reporting 113

Reporting Data Quality Strategy Data-driven 113

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

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 66

Data Quality Data Integration Metadata Cost-Benefit 66

Sisense

SEPTEMBER 3, 2020

They are the link between the data resources available to an enterprise and executives looking for opportunities to make the business better, faster, and stronger. Data Analyst. 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

Peter James Thomas

OCTOBER 30, 2018

Most of the time, the article does nothing more than to reflect the continuing confusion about whether or not organisations need CDOs and – assuming that they do – what their remit should be and who they should report to [4]. It may be to build a new (or a first) Data Architecture. It may be to improve Data Quality.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

CIO Business Intelligence

FEBRUARY 20, 2023

To earn this cert, candidates should know how to maintain and modify Sales Cloud and Service Cloud applications; manage users, data, and security; and construct dashboards, reports, and workflows. The certification emphasizes testing, governance, and integration with external systems within an organization’s infrastructure.

Consulting 69

Consulting B2B Cost-Benefit Sales 69

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. This required additional investments in metadata.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. A DataOps implementation project consists of three steps.

Testing 152

Testing Metadata Dashboards Statistics 152

erwin

OCTOBER 24, 2019

As a result, the applications and initiatives that depend on a solid data infrastructure may be compromised, leading to faulty analysis and insights. Metadata Is the Heart of Data Intelligence. Organizations then can take a data-driven approach to business transformation , speed to insights, and risk management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

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 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud.

Data Strategy 71

Data Strategy Strategy Data Warehouse Prescriptive Analytics 71

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 115

Data Lake Unstructured Data Data Warehouse Data Quality 115

CIO Business Intelligence

JULY 28, 2023

At the same time, it reduces risk by ensuring that all data is under control, avoiding inconsistencies, and adhering to a single source of truth. In a recent IDC Infobrief , more than half of respondents report that regulatory compliance is a primary factor in deciding how and where they store enterprise data.

Risk 92

Risk Management Cost-Benefit Data mining 92

IBM Big Data Hub

DECEMBER 4, 2023

The platform has been used to modernize and unify the information technology (IT) ecosystem of major financial firms, simplify human capital management (HCM) across brands’ subsidiaries, and optimize reporting processes in complex healthcare settings. Data quality: Ensure migrated data is clean, correct and current.

Testing 75

Testing Consulting Digital Transformation Cost-Benefit 75

Peter James Thomas

MAY 3, 2019

Collation of Data to provide Information. This area includes what is often described as “traditional” reporting [3] , Dashboards and analysis facilities. Control of Data to ensure it is Fit-for-Purpose. Data Architecture / Infrastructure. I will start at the top left and work across and then down.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

Cloudera

SEPTEMBER 7, 2023

The way to manage this is by embedding data integration, data quality-monitoring, and other capabilities into the data platform itself , allowing financial firms to streamline these processes, and freeing them to focus on operationalizing AI solutions while promoting access to data, maintaining data quality, and ensuring compliance.

Insurance 78

Insurance Risk Data-driven Finance 78

CIO Business Intelligence

FEBRUARY 28, 2024

Even in its infancy, gen AI has become an accepted course of action and application, and the most common use cases include automation of IT processes, security and threat detection, supply chain intelligence, and automating customer service and network processes, according to a report released by IBM in January.

IT 127

IT Consulting Modeling Enterprise 127

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 89

Data Lake Analytics Snapshot Optimization 89

Ontotext

MAY 30, 2019

Let’s imagine Johnny Mnemonic – Keanu Reeves’ character from the cyberpunk action thriller movie of the same name – who is carrying a data package inside his head. He has been tasked with smuggling data – not in the 90s as the movie had it, but these days. 6 Linked Data, Structured Data on the Web.

Cost-Benefit 87

Cost-Benefit Technology Big Data Metadata 87

Ontotext

MAY 30, 2019

Let’s imagine Johnny Mnemonic – Keanu Reeves’ character from the cyberpunk action thriller movie of the same name – who is carrying a data package inside his head. He has been tasked with smuggling data – not in the 90s as the movie had it, but these days. 6 Linked Data, Structured Data on the Web.

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75

Andrew White

JANUARY 9, 2022

First, how we measure emissions and carbon footprint is about data design and policy. For example I would argue that most organizations that report their carbon footrest are not doing it consistently and nor are they doing it correctly. We have a lot of data literacy material published and we annually update our must-have roles work.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Alation

JANUARY 25, 2022

In a practical sense, a modern data catalog should capture a broad array of metadata that also serves a broader array of consumers. In concrete terms, that includes metadata for a broad array of asset classes, such as BI reports, business metrics, business terms, domains, functional business processes, and more.

Metadata 52

Metadata IT Metrics Data-driven 52

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. Master Data – additional definition (contributor: Scott Taylor ).

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69