IBM Big Data Hub

FEBRUARY 6, 2024

Through the development of cyber recovery plans that include data validation through custom scripts, machine learning to increase data backup and data protection capabilities, and the deployment of virtual machines (VMs) , companies can recover from cyberattacks and prevent re-infection by malware in the future.

Cost-Benefit 89

Cost-Benefit Testing Risk Strategy 89

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. .” – Take A Bow, Rihanna (I may have heard it wrong) Validating data quality at rest is critica l to the overall success of any Data Journey. The image above shows an example ‘’data at rest’ test result.

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. 6] Debugging may focus on a variety of failure modes (i.e.,

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

CIO Business Intelligence

JANUARY 9, 2024

ChatGPT caused quite a stir after it launched in late 2022, with people clamoring to put the new tech to the test. Our firm’s leaders] wanted to make sure there were guidelines in place to protect the company, its data, and its people.” 1 among the top three risks — followed by statistical validity and model accuracy.

IT 127

IT Risk Cost-Benefit Enterprise 127

Smart Data Collective

OCTOBER 26, 2023

AI poses a number of benefits and risks for modern businesses. A successful breach can result in loss of money, a tarnished brand, risk of legal action, and exposure to private information. Cybersecurity aims to stop malicious activities from happening by preventing unauthorized access and reducing risks.

Technology 91

Technology Risk Measurement IoT 91

CIO Business Intelligence

MAY 14, 2024

Controlling escalating cloud and AI costs and preventing data leakage are the top reasons why enterprises are eying hybrid infrastructure as their target AI solution. But the company’s critical data — and any future generative AI data — will likely run on its new hosted private cloud, says Andrew Cotter, Somerset’s EVP and CIO. “As

IT 141

IT Data Processing Enterprise Modeling 141

erwin

OCTOBER 8, 2020

No less daunting, your next step is to re-point or even re-platform your data movement processes. And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. The metadata-driven suite automatically finds, models, ingests, catalogs and governs cloud data assets.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

DataKitchen

OCTOBER 2, 2023

.’ What’s a Data Journey? Data Journeys track and monitor all levels of the data stack, from data to tools to code to tests across all critical dimensions. A Data Journey supplies real-time statuses and alerts on start times, processing durations, test results, and infrastructure events, among other metrics.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

Cloudera

JUNE 22, 2023

It ensures compliance with regulatory requirements while shifting non-sensitive data and workloads to the cloud. Its built-in intelligence automates common data management and data integration tasks, improves the overall effectiveness of data governance, and permits a holistic view of data across the cloud and on-premises environments.

Cost-Benefit 66

Cost-Benefit Digital Transformation Data Governance Unstructured Data 66

IBM Big Data Hub

DECEMBER 4, 2023

In May, the European Union Aviation Safety Agency (EASA) released the second version of its AI Roadmap , which provides a comprehensive plan for the integration of AI in aviation, with a focus on safety, security, AI assurance, human factors and ethical considerations. Generative AI can build digital twins much faster than current methods.

Optimization 68

Optimization Testing Machine Learning Measurement 68

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

erwin

JANUARY 11, 2019

Consider the problematic issue of manually mapping source system fields (typically source files or database tables) to target system fields (such as different tables in target data warehouses or data marts). So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

CIO Business Intelligence

JUNE 7, 2022

Prescriptive analytics is a type of advanced analytics that involves the application of testing and other techniques to recommend specific solutions that will deliver desired outcomes. It is frequently used for risk analysis. In business, predictive analytics uses machine learning, business rules, and algorithms.

Data Analytics 131

Data Analytics Diagnostic Analytics Management Analytics 131

erwin

JANUARY 24, 2019

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. It also can populate and maintain Big Data sets by generating PIG, Scoop, MapReduce, Spark, Python scripts and more.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

Jedox

SEPTEMBER 3, 2020

The new normal introduced new risks from employee health and safety, supply chain stress and government mandates – all with working capital implications. Cloud scenario planning platforms can now capture financial data and sub-ledger transactions in real time to provide constant feedback on cost and revenue.

Uncertainty 81

Uncertainty Forecasting Digital Transformation Risk 81

Dataiku

FEBRUARY 19, 2019

You're testing the boundaries of your business's technological capacity and your ability to change at the same time. If your POC is an anomaly or you're unprepared to activate it, you risk missing out on technology that could keep your business on top. POCs often feel like a gamble.

Testing 49

Testing Data Integration Risk Technology 49

erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. Click here to test drive of the new erwin DM.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

Jet Global

JANUARY 4, 2021

Planners began to integrate functional and departmental plans into their own forecasts. Coronavirus was a frighteningly effective stress test in many ways for organizations’ resilience. Speed was one of the main qualities tested. Planners realized where they need the most support. Want to learn more? Sources: [link].

Forecasting 98

Forecasting Finance Testing Sales 98

IBM Big Data Hub

SEPTEMBER 20, 2022

Alongside the significant brand reputation risk, there’s also a growing set of data and AI regulations across the world and across industries — like the upcoming European Union AI Act — that companies must adhere to. Similarly, facts can be collected while the model is in the testing and validation stages.

Metadata 56

Metadata Machine Learning Data-driven Modeling 56

CIO Business Intelligence

OCTOBER 13, 2022

Too often IT initiatives are undertaken solely as technical projects, with only loose affiliation with line-of-business stakeholders, ushering in the risk of drifting too far from the overall goals and business objectives of the organization. This is followed by an end-to-end testing upgrading from component,” Kumar says. “If

ROI 129

ROI IT Sales Consulting 129

Smart Data Collective

SEPTEMBER 26, 2019

These approaches operate under the assumption that validation must be carried out as soon as possible consequently minimizing exposure risk as in the course of any project. Data Integration. Data integration is key for any business looking to keep abreast with the ever-changing technology landscape.

Big Data 80

Big Data Software Unstructured Data Data Integration 80

CIO Business Intelligence

SEPTEMBER 2, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The average salary for a financial software engineer is $116,670 per year, with a reported salary range of $85,000 to $177,000 per year, according to data from Glassdoor. Full-stack software engineers are essentially high-level software engineers who are focused on designing, testing, and implementing software applications.

Finance 98

Finance IT Software Reporting 98

AWS Big Data

JUNE 28, 2023

Furthermore, the time required to build or change pipelines makes the data unfit for near-real-time use cases such as detecting fraudulent transactions, placing online ads, and tracking passenger train schedules.

Analytics 69

Analytics Data Warehouse Data Lake Data-driven 69

CIO Business Intelligence

JUNE 7, 2022

You don’t understand how long you should test your feature and what exactly you should measure,” he says. Data scientists may build the ML models, but its ML engineers who implement them. An ML engineer is also involved with validation of models, A/B testing, and monitoring in production.”. Data steward. ML engineer.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

IBM Big Data Hub

APRIL 12, 2022

Mitigating risk. A CDO’s priority is not just to learn the strategic needs of the business and senior leadership, but also to implement a data strategy that helps leaders achieve their goals faster and embrace data as a competitive advantage. Expanding the bottom line by making operations more efficient.

Data Strategy 77

Data Strategy Strategy Enterprise Data-driven 77

Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Add the predictive logic to the data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Sisense

SEPTEMBER 23, 2019

If it breaks, it puts at risk, not just a single application, but an entire chain of business processes built around it. Once we have a solid foundation of unit tests which cover individual functions, API tests provide higher reliability covering an interface closer to the user, yet without the brittleness of UI tests.

Testing 89

Testing Strategy Modeling ROI 89

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Cloudera

AUGUST 31, 2021

Smart DwH Mover helps in accelerating data warehouse migration. Smart Data Validator helps in extensive data reconciliation and testing. Here is the flow of events during migration by leveraging tools from Smart Data Transition Toolkit. Smart Query Convertor converts queries and views to be made compatible on CDW.

Data Warehouse 83

Data Warehouse Cost-Benefit Metadata Data-driven 83

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. Don’t they all do the same thing? Is this the paradox of choice?

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

DataKitchen

NOVEMBER 18, 2021

Write tests that catch data errors. Build observability and transparency into your end-to-end data pipelines. We talk about systemic change, and it certainly helps to have the support of management, but data engineers should not underestimate the power of the keyboard. Automate manual processes. Implement DataOps methods.

Testing 246

Testing Data Governance Measurement Software 246

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

Insurance 84

Insurance Risk Data-driven Finance 84

Smart Data Collective

FEBRUARY 14, 2023

They test the product and find bugs that turn customers away. Game analysts are exclusively engaged in testing and reporting, and the elimination of identified problems falls on the shoulders of the development team. Data integrity control. Creation of hypotheses and their testing.

Big Data 117

Big Data Data Analytics Analytics Testing 117

DataKitchen

OCTOBER 25, 2022

When considering how organizations handle serious risk, you could look to NASA. The space agency created and still uses “mission control” where many screens share detailed data about all aspects of a space flight. Any data operation, regardless of size, complexity, or degree of risk, can benefit from DataOps Observability.

Testing 130

Testing Data-driven Visualization Dashboards 130

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. Probably the best one-liner I’ve encountered is the analogy that: DG is to data assets as HR is to people. In other words, data can only be persisted if it is first encrypted.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process.

Data Analytics 91

Data Analytics Analytics Data Warehouse Data Lake 91