Octopai

DECEMBER 11, 2022

Banks didn’t accurately assess their credit and operational risk and hold enough capital reserves, leading to the Great Recession of 2008-2009. Let’s take a look at several regulatory standards and explore automated data lineage’s role in smoothing and improving data compliance. Data lineage and financial risk data compliance.

Insurance 52

Insurance Risk Metadata Reporting 52

Cloudera

JUNE 1, 2021

In summary, the next chapter for Cloudera will allow us to concentrate our efforts on strategic business opportunities and take thoughtful risks that help accelerate growth. Datacoral powers fast and easy data transformations for any type of data via a robust multi-tenant SaaS architecture that runs in AWS.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

TDAN

JUNE 15, 2021

We have seen an impressive amount of hype and hoopla about “data as an asset” over the past few years. And one of the side effects of the COVID-19 pandemic has been an acceleration of data transformation in organisations of all sizes.

Data Transformation 98

Data Transformation Management Risk Management Risk 98

datapine

SEPTEMBER 29, 2022

Data processes that depended upon the previously defective data will likely need to be re-initiated, especially if their functioning was at risk or compromised by the defected data. This is also the point where data quality rules should be reviewed again. date, month, and year).

Data Quality 241

Data Quality Metrics Data-driven Management 241

TDAN

MARCH 16, 2021

Taking Stock A year ago, organisations of all sizes around the world were catapulted into a cycle of digital and data transformation that saw many industries achieve in a matter of weeks in what would otherwise have taken many years to achieve. Small businesses pivoted to doing business online in a way that they might […].

Data Transformation 98

Data Transformation Risk Management Risk Data Strategy 98

datapine

MAY 2, 2023

However, if you underestimate how many vehicles a particular route or delivery will require, then you run the risk of giving customers a late shipment, which negatively affects your client relationships and brand image. After examining their data, UPS found that trucks turning left were costing them a lot of money.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

erwin

APRIL 29, 2020

Compliance with these business rules can be tracked through data lineage, incorporating auditability and validation controls across data transformations and pipelines to generate alerts when there are non-compliant data instances. Data lineage offers proof that the data provided is reflected accurately.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics? It is frequently used for risk analysis.

Data Analytics 131

Data Analytics Diagnostic Analytics Management Analytics 131

erwin

SEPTEMBER 17, 2020

Regulatory compliance places greater transparency demands on firms when it comes to tracing and auditing data. Business terms and data policies should be implemented through standardized and documented business rules.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Sisense

AUGUST 28, 2020

Data integrity looks at the whole life cycle for your data and considers the processes around how it’s generated, stored, accessed, and applied to accomplish specific business tasks. Throughout that life cycle, a good data integrity program aims to ensure that data is available, complete and accurate.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

Alation

MARCH 22, 2022

So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY? They can better understand data transformations, checks, and normalization. They can better grasp the purpose and use for specific data (and improve the pipeline!). IDF provides a focused, business-driven solution.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

IBM Big Data Hub

JULY 28, 2023

Since its launch in 2020, DATA ONE has been successfully adopted by multinational companies across sectors, including insurance and banking, automotive, energy and utilities, manufacturing, logistics and telco. DATA ONE consists of three modules that can be activated as needed: Data Mover , a secure file-transfer enterprise solution.

Data Integration 60

Data Integration Optimization Software Insurance 60

DataKitchen

JULY 27, 2023

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. Azure Machine Learning).

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CDW Research Hub

JANUARY 22, 2020

While the looming threat of hackers and security breaches should not be taken lightly, the good news is companies can mitigate risks commonly associated with breaches and safely migrate their database(s) to the cloud with proper planning, insight and preventive measures. So how do you keep your business out of the security breach headlines?

Measurement 52

Measurement Consulting Risk Finance 52

AWS Big Data

JUNE 6, 2023

By establishing and configuring alerts and notifications, you can actively monitor data quality and receive timely alerts when data quality issues are identified. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

Data Quality 71

Data Quality Metrics Data-driven Visualization 71

AWS Big Data

MAY 16, 2023

Data collection and processing are handled by a third-party smart sensor manufacturer application residing in Amazon Virtual Private Cloud (Amazon VPC) private subnets behind a Network Load Balancer. The AWS Glue Data Catalog contains the table definitions for the smart sensor data sources stored in the S3 buckets.

Dashboards 74

Dashboards Statistics Data Collection Business Intelligence 74

Alation

FEBRUARY 2, 2023

Having the right tools is essential for any successful data product manager focused on enterprise data transformation. When choosing the tools for a project, whether it be the CIO , CDO , or data product managers themselves, the buyers must see the big picture. You might even call them data storytellers!

Management 52

Management Data-driven Visualization Strategy 52

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. To mitigate risks, it’s important to run as many data integration processes as possible on internal servers.

Enterprise 78

Enterprise Data Integration Data Quality Contextual Data 78

DataKitchen

DECEMBER 9, 2022

In addition to speeding up the development and deployment of data-driven solutions, DataOps automation also helps organizations to improve the quality and reliability of their data-related workflows. The data scientists and IT professionals were starting to get frustrated, when suddenly, a magical fairy appeared out of nowhere.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Ontotext

APRIL 4, 2019

But still, is there a risk that AI could replace people at their workplace? Milena Yankova : The professions of the future are related to understanding and processing data, transforming it into information and extracting knowledge from it. This is a knowledge that anyone can get, but it would take much longer than optimal.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

DataKitchen

OCTOBER 5, 2022

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 176

Testing Risk Data Processing Statistics 176

DataKitchen

OCTOBER 5, 2022

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 130

Testing Risk Data Processing Statistics 130

IBM Big Data Hub

MARCH 14, 2024

For existing IBM on-premises database customers, transitioning to AWS is seamless, offering risk-free, like-for-like upgrades. Integrate seamlessly with watsonx.data SaaS and other IBM and AWS services like IBM data fabric, Amazon S3, Amazon EMR, AWS Glue and more to scale analytics and AI workloads across the enterprise. Existing

Cost-Benefit 82

Cost-Benefit Metadata Optimization Management 82

CIO Business Intelligence

JUNE 23, 2022

The concept of supply chain visibility and sourcing applies to data supply chains just as well as physical supply chain management. Understanding the sources of data, any transformation activities that take place as well as the “customer lead time” helps organizations identify and mitigate risks. Supply chain complexity.

Data Quality 96

Data Quality Key Performance Indicator Metrics KPI 96

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

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

OCTOBER 11, 2023

This is due to the complexity of the JSON structure, contracts, and the risk evaluation process on the payor side. Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92

Alation

JUNE 28, 2022

Scale effectively: Leverage taxonomies to ensure consistent modeling outcomes when introducing new data sets or changing business demands. Track data lineage: Document data origins, record data transformation and movement, and visualize flow throughout the entire data lifecycle.

Metadata 52

Metadata Management Data Governance Machine Learning 52

O'Reilly on Data

JANUARY 17, 2023

Instead of invoking the open-source scikit-learn or Keras calls to build models, your team now goes from Pandas data transforms straight to … the API calls for AWS AutoPilot or GCP Vertex AI. That is: what model risk does the company face?) It does not exist in the code. AutoML drives this point home.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

AWS Big Data

APRIL 12, 2023

However, SHJs have drawbacks, such as risk of out of memory errors due to its inability to spill to disk, which prevents them from being aggressively used across Spark in place of SMJs by default. About the Authors Melody Yang is a Senior Big Data Solution Architect for Amazon EMR at AWS.

Testing 71

Testing Big Data Metadata Optimization 71

CIO Business Intelligence

JUNE 14, 2022

I think that speaks volumes to the type of commitment that organizations have to make around data in order to actually move the needle.”. So if funding and C-suite attention aren’t enough, what then is the key to ensuring an organization’s data transformation is successful? Analytics, Chief Data Officer, Data Management

Data Transformation 143

Data Transformation Data-driven Data Strategy Strategy 143

Alation

OCTOBER 28, 2021

Leaders are asking how they might use data to drive smarter decision making to support this new model and improve medical treatments that lead to better outcomes. Yet this is not without risks. To use that information compliantly, data teams must work within a transparent governance framework.

Data Governance 52

Data Governance Measurement Modeling Metrics 52

Sisense

AUGUST 6, 2020

AI can add value to your product/service in many ways, including: Improved business performance Reduced costs Increased customer satisfaction Improved brand value Risk reduction (reduced human error, fraud reduction, spam reduction) Improved convenience and accessibility of products. What are the right KPIs and outputs for your product?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

AWS Big Data

JULY 25, 2023

Follow security best practices by using a strong password policy and regular password rotation to reduce the risk of password-based attacks or exploits. As well as Talend Cloud for enterprise-level data transformation needs, you could also use Talend Stitch to handle data ingestion and data replication to Redshift Serverless.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever.

Metadata 52

Metadata ROI Optimization Data Quality 52

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Their costs were climbing.

Cost-Benefit 55

Cost-Benefit Informatics Optimization Management 55

Octopai

NOVEMBER 23, 2020

In fact, the LIBOR transition program marks one of the largest data transformation obstacles ever seen in financial services. Building an inventory of what will be affected is a huge undertaking across all of the data, reports, and structures that must be accounted for. A New Approach to Enterprise Business Intelligence.

Metadata 54

Metadata Enterprise Business Intelligence Data Governance 54