erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. In fact, many commonly accepted best practices for designing OLTP databases could well be considered worst practices for these purely analytical systems. Analytical. Business Focus.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

AWS Big Data

FEBRUARY 1, 2024

Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization. This will be your OLTP data store for transactional data. version cluster.

Data Warehouse 122

Data Warehouse Dashboards Risk Management Risk 122

Timo Elliott

MAY 27, 2022

I was at the Gartner Data & Analytics conference in London a couple of weeks ago and I’d like to share some thoughts on what I think was interesting, and what I think I learned…. First, data is by default, and by definition, a liability , because it costs money and has risks associated with it.

Data Analytics 124

Data Analytics Analytics Recreation/Entertainment Data Lake 124

AWS Big Data

MAY 28, 2024

Welcome back to our exciting exploration of architectural patterns for real-time analytics with Amazon Kinesis Data Streams! Before we dive in, we recommend reviewing Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1 for the basic functionalities of Kinesis Data Streams.

IoT 90

IoT Analytics Dashboards Data-driven 90

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

Laminar Security

JULY 19, 2023

To effectively protect sensitive data in the cloud, cyber security personnel must ensure comprehensive coverage across all their environments; wherever data travels, including cloud service providers (CSPs), data warehouses, and software-as-a-service (SaaS) applications.

Data Warehouse 91

Data Warehouse Data-driven Data Governance Risk 91

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Two problems arise.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Jet Global

DECEMBER 8, 2020

If your company is planning to implement Microsoft’s Power BI analytics platform , it is critically important that you understand the complexity involved with a complete implementation. A full Power BI implementation is a large-scale project, and it carries similar risks. Power BI Without the Risk. Power BI Is Highly Complex.

Finance 52

Finance Risk Reporting Software 52

Cloudera

OCTOBER 4, 2023

In financial services, fast-moving data is critical for real-time risk and threat assessments. We can move to predictive fraud and breach prevention, greatly increasing the protection of customer data and financial assets. Without real-time analytics we won’t catch the threats until after they’ve caused significant damage.

Data Warehouse 88

Data Warehouse Experimentation Cost-Benefit Dashboards 88

AWS Big Data

APRIL 29, 2024

This system simplifies managing user access, saves time for data security administrators, and minimizes the risk of configuration errors. Addressing big data challenges – Big data comes with unique challenges, like managing large volumes of rapidly evolving data across multiple platforms.

Management 95

Management Big Data Metadata Data Warehouse 95

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 81

Data Warehouse Cost-Benefit Metadata Data-driven 81

BizAcuity

NOVEMBER 22, 2022

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

Cloudera

NOVEMBER 12, 2020

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. Key areas of concern are: .

Data Warehouse 104

Data Warehouse Reporting Risk Cost-Benefit 104

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. AWS’s secure and scalable environment ensures data integrity while providing the computational power needed for advanced analytics.

Insurance 78

Insurance Data Warehouse Data-driven Unstructured Data 78

CIO Business Intelligence

JUNE 12, 2024

As part of its transformation, UK Power Networks partnered with Databricks, Tata Consulting Services, Moringa Partners, and others to not only manage the cloud migration but also help integrate IoT devices and smart meters to deliver highly granular, real-time analytics.

Digital Transformation 97

Digital Transformation Cost-Benefit Forecasting Marketing 97

Cloudera

NOVEMBER 1, 2022

These systems can pose operational risks, including rising costs and the inability to meet mission requirements. . In the private sector, excluding highly regulated industries like financial services, the migration to the public cloud was the answer to most IT modernization woes, especially those around data, analytics, and storage.

Cost-Benefit 88

Cost-Benefit Data Architecture Risk IoT 88

AWS Big Data

MAY 30, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It served many enterprise use cases across API feeds, content mastering, and analytics interfaces.

Data Warehouse 85

Data Warehouse Data Lake Cost-Benefit Structured Data 85

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? Fortunately, advances in analytic technology have made the ability to see reliably into the future a reality.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. In this way, the Cloud Data Warehouse Accelerator enables a seamless transition to Snowflake. Mitigate risks with a seamless cloud migration. Contact us to learn more.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. Create a Redshift table and load local feature data into the table. The data warehouse team ingests and analyzes transaction data in a Redshift table, owned by them.

Modeling 62

Modeling Data Warehouse Machine Learning Testing 62

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. The user permissions are evaluated using AWS Lake Formation to filter the relevant data.

Data Governance 94

Data Governance Unstructured Data Metadata Data Lake 94

BizAcuity

APRIL 1, 2023

This typically requires a data warehouse for analytics needs that is able to ingest and handle real time data of huge volumes. Snowflake is a cloud-native platform that eliminates the need for separate data warehouses, data lakes, and data marts allowing secure data sharing across the organization.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

Alation

FEBRUARY 13, 2020

We also have some primary insurance entities in the group, but the main thing about reinsurance is that we’re taking care of the big and complex risks in the world. I know in February of 2017 Munich Re launched their own innovative platform as a cornerstone for analytics that involved a big data lake and a data catalog.

Data-driven 52

Data-driven Data Lake Enterprise Analytics 52

datapine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. They prevent you from drowning in data.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

Laminar Security

DECEMBER 13, 2023

Close to 70% of respondents in an ISC report indicated that they believe their organization lacks requisite cybersecurity staff to handle cloud data risk effectively. Learn in this article how Laminar harnesses AI for data discovery and classification and reduces public cloud data risks.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

Sisense

JUNE 8, 2020

Datasets are on the rise and most of that data is on the cloud. The answer is “cloud-first analytics.” The recent rise of cloud data warehouses like Snowflake means businesses can better leverage all their data using Sisense seamlessly with products like the Snowflake Cloud Data Platform to strengthen their businesses.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

Cloudera

AUGUST 2, 2018

True – millions of credit card transactions are processed within minutes for consistency, fraud and compliance, using petabytes of historical transactions as reference data. Leading insurers are underwriting policies with lower risks. We call it ‘Modern Data Warehousing’. Banks know more about their customers today.

Data Warehouse 51

Data Warehouse Insurance Experimentation Software 51

CIO Business Intelligence

SEPTEMBER 26, 2023

The new platform would alleviate this dilemma by using machine learning (ML) algorithms, along with source data accessed by SAP’s Data Warehouse Cloud. Analytics would allow users to gain immediate insights into circumstances. As a result, total load calculations were not being provided to the grid control center in time.

Machine Learning 93

Machine Learning Forecasting Measurement Data Warehouse 93

Alation

JULY 28, 2022

The cloud is no longer synonymous with risk. There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. Migrate What Matters.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

erwin

APRIL 2, 2021

With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Lack of a solid data governance foundation increases the risk of data-security incidents.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Timo Elliott

OCTOBER 3, 2019

Thankfully, most avoided this kind of opening, which plagues analytics presentations to this day! “Did you know there’s more data THAN EVER BEFORE?!” And because if companies or IT departments don’t implement them, they risk losing their roles to someone who will! People, collaboration, and ease of use.

Data Warehouse 69

Data Warehouse Digital Transformation Machine Learning Strategy 69

Sisense

MARCH 27, 2019

To get the most out of data, companies need to analyze it as soon as it is created—when it can provide the most immediate and relevant insights. Unlike traditional models that look at historical data for patterns, real-time analytics focuses on understanding information as it arrives to help make faster, better decisions.

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

Cloudera

JANUARY 28, 2022

As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts.

Slice and Dice 114

Slice and Dice Cost-Benefit Risk Data Governance 114

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics. Enterprise Business Intelligence.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

AWS Big Data

JANUARY 24, 2023

Serverless applications are a modernized way to perform analytics among business departments and engineering teams. Reporting and analysis – An application where you can trigger large analytical queries with dynamic inputs and then view or download the results. What are WebSockets and why do we need them?

Analytics 58

Analytics Data-driven Management Reporting 58

Cloudera

OCTOBER 11, 2022

Risk increases. Data and AI projects cost more and take longer. This leads to the obvious question – how do you do data at scale ? Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. And they all need lots of data.

Snapshot 94

Snapshot Data Science Digital Transformation Metadata 94