AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 56

Data-driven Enterprise Data Governance Data Lake 56

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. A lot of people in our audience are looking at implementing data lakes or are in the middle of big data lake initiatives.

Data-driven 52

Data-driven Data Lake Enterprise Analytics 52

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

erwin

OCTOBER 31, 2019

Data security incidents may be the result of not having a true data governance foundation that makes it possible to understand the context of data – what assets exist and where, the relationship between them and enterprise systems and processes, and how and by what authorized parties data is used. No Hocus Pocus.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

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. This enables organizations to connect to any data source and combine any type of data. Mitigate risks with a seamless cloud migration.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

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

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

OCTOBER 6, 2022

Certain technologies require skills to maintain them that are harder to find, which is a further risk as those resources move towards retirement age. Optimize automation: AI and machine learning (ML) are now the key terms here, but RPA (Robotic Process Automation) still has its place in driving efficiency throughout the enterprise.

Digital Transformation 91

Digital Transformation Cost-Benefit Data Lake Machine Learning 91

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

Cloudera

SEPTEMBER 2, 2020

Additionally, lines of business (LOBs) are able to gain access to a shared data lake that is secured and governed by the use of Cloudera Shared Data Experience (SDX). According to 451 Research’s Voice of the Enterprise: Cloud, Hosting & Managed Services study, 58% of Enterprises are moving towards a hybrid IT environment.

Cost-Benefit 69

Cost-Benefit Data Warehouse Data Lake Machine Learning 69

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

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

CIO Business Intelligence

APRIL 6, 2022

Enterprises are increasingly moving towards bringing together a human-centric experience with innovations led by cutting-edge technologies. While enterprises invest in innovation, key challenges such as successful sustenance, ROI realization, scaling and accelerating still remain. . Accelerate Innovation. Navigate Your Next Innovation.

Experimentation 102

Experimentation Data Lake Uncertainty Enterprise 102

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. Given the risks of staying intact to primitive practices is scary in itself.

Management 66

Management Data Lake Uncertainty Data Warehouse 66

CIO Business Intelligence

SEPTEMBER 6, 2022

When Steve Pimblett joined The Very Group in October 2020 as chief data officer, reporting to the conglomerate’s CIO, his task was to help the enterprise uncover value in its rich data heritage. As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence.

IT 97

IT Forecasting Data Lake Enterprise 97

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. Read more about last years Data Impact Award winners. SECURITY AND GOVERNANCE LEADERSHIP.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

CIO Business Intelligence

APRIL 12, 2023

Most current data architectures were designed for batch processing with analytics and machine learning models running on data warehouses and data lakes. Previously, he built high-performance teams for data-value driven initiatives at organizations including Charles Schwab, Overstock, and VMware.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

Jet Global

JANUARY 18, 2021

Perhaps more importantly, it provides an opportunity for the organization to implement measures in advance that can reduce risk, lower costs, and improve the end result. Because they are separate from the core ERP application, there is no risk that they will corrupt that core functionality. Start with a Functional Review.

Data Lake 98

Data Lake Reporting Cost-Benefit Finance 98

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

JANUARY 6, 2021

Microsoft D365 F&SCM is targeted at mid-sized enterprises, while Microsoft D365 BC is a good fit for smaller businesses with simpler requirements. Getting to the cloud, though, will require one more big project, with all of the cost, complexity, and risk that go along with such endeavors.

Cost-Benefit 98

Cost-Benefit Testing Finance Reporting 98

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

SEPTEMBER 8, 2022

“The enormous potential of real-time data not only gives businesses agility, increased productivity, optimized decision-making, and valuable insights, but also provides beneficial forecasts, customer insights, potential risks, and opportunities,” said Krumova.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. Instead, we can use automation to speed up the process of migration and reduce heavy lifting tasks, costs, and risks. He is passionate about big data and data analytics.

Metadata 80

Metadata Testing Data Lake Consulting 80

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning in marketing and sales According to Forbes , marketing and sales teams prioritize AI and ML more than any other enterprise department. Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). Antivirus programs may use AI and ML techniques to detect and block malware.

Machine Learning 49

Machine Learning Marketing Forecasting Modeling 49

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

In(tegrate) the Clouds

DECEMBER 21, 2015

On its most recent earnings call, financial analysts noted that, “cloud is the epicenter of the growth story,” which represents the ultimate tipping point for enterprise cloud computing adoption. 2016 will be the year of the data lake. What are the biggest risks for software vendors in 2016? Read all of the answers.

Technology 45

Technology Internet of Things Digital Transformation Software 45

Peter James Thomas

JUNE 20, 2019

An obvious parallel in my world is to consider another business activity that reached peak popularity in the 2000s, Data Warehouse programmes [4]. Figures suggest that both BPR and Data Warehouse programmes have a failure rate of 60 – 70% [5]. For example in 20 Risks that Beset Data Programmes. . [7].

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 101

Data Warehouse Data Lake Analytics Machine Learning 101

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 100

Data Lake Data Warehouse Management Risk 100

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. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 91

Data Analytics Analytics Data Warehouse Data Lake 91

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). for DG adoption in the enterprise. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. And you also already know siloed data is costly, as that means it will be much tougher to derive novel insights from all of your data by joining data sets.

Data Lake 94

Data Lake Data Warehouse IT Analytics 94

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. 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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

OCTOBER 19, 2022

The CIO’s evolving data role Data falls into a similar category as digital. CIOs are responsible for building an enterprise data and analytics capability, but they do not own data as a function. If that is the case, where should the data and analytics function sit? What about risk?

IT 125

IT Digital Transformation Data Warehouse Risk 125

DataKitchen

JULY 27, 2023

Azure Synapse Analytics Pipelines: Azure Synapse Analytics (formerly SQL Data Warehouse) provides data exploration, data preparation, data management, and data warehousing capabilities. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130