Alation

MAY 19, 2022

Alation attended last week’s Gartner Data and Analytics Summit in London from May 9 – 11, 2022. Coming off the heels of Data Innovation Summit in Stockholm, it’s clear that in-person events are back with a vengeance, and we’re thrilled about it. Establish what data you have. Leverage small data.

Metadata 52

Metadata Data Analytics Analytics Data Governance 52

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

Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This universe of metadata represents a treasure trove of connected information.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

Cloudera

MARCH 3, 2022

It’s believed the source of the breach was Marriott’s Starwood subsidiary and Marriott might not have done due diligence when merging its newly acquired subsidiary’s data into its own databases. In 2017, Anthem reported a data breach that exposed thousands of its Medicare members. Better Data Governance: A Hybrid Solution.

Data Governance 101

Data Governance Enterprise Data Quality Metadata 101

DataKitchen

AUGUST 3, 2021

Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools. It’s no fun working in data analytics/science when you are the bottleneck in your company’s business processes. See the pattern? The problem is not “you.”

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Ontotext

JANUARY 29, 2024

As companies in almost every market segment attempt to continuously enhance and modernize data management practices to drive greater business outcomes, organizations will be watching numerous trends emerge this year. Sometimes, the challenge is that the data itself often raises more questions than it answers.

Strategy 52

Strategy Management Metadata Data-driven 52

CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

MARCH 4, 2024

In this way, data may just be the ultimate disruptor – a fact that the insurance industry knows all too well. As data volumes continue to increase alongside a correlating number of business requests, modern insurance data leaders face a nuanced set of challenges. Enter data mesh.

Insurance 91

Insurance Strategy Data Governance Data Integration 91

erwin

JANUARY 30, 2020

Digital transformation and data standards/uniformity round out the top five data governance drivers, with 37 and 36 percent, respectively. Constructing a Digital Transformation Strategy: How Data Drives Digital. However, more than 50 percent say they have deployed metadata management, data analytics, and data quality solutions.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? Here is a sample graphic from the document that covers the end-to-end data and analytics architecture on GCP: My analysis of GCP revealed some of its core strengths and weaknesses. This is the focus of my latest research which published in Jan 2019.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

IBM Big Data Hub

JUNE 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Here are a few common data management challenges: Regulatory compliance on data use.

Data-driven 56

Data-driven Enterprise Data Governance Data Lake 56

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Answers will differ widely depending upon a business’ industry and strategy for growth.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Ontotext

JANUARY 26, 2023

For all these data operations to flow smoothly, data needs to be interoperable, of good quality and easy to integrate. In other words, data coming from different sources need to be interlinked, contextualized and normalized in a graph that allows for its consistent and unambiguous interpretation.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

AWS Big Data

NOVEMBER 6, 2023

Setup and Teardown tasks It’s common to build workflows that require ephemeral resources, for example an S3 bucket to temporarily store data, databases and corresponding datasets to run quality checks, or a compute cluster to train a model in a machine learning (ML) orchestration pipeline. Doing this manually is complex.

Metrics 103

Metrics Metadata Snapshot Management 103

CIO Business Intelligence

MARCH 29, 2022

The same principle applies to getting value from data. Organizations may acquire a lot of data, but they aren’t getting much value from it. It is estimated that nearly 75% of the data that enterprises collect remains unused, and thus, the value is not realized. What is data waste, and why does it happen?

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Ontotext

NOVEMBER 18, 2021

You step onto the market, and if you don’t keep your data, there’s no knowing where you might be swept off to. [1]. Picture this – you start with the perfect use case for your data analytics product. Nowadays, data analytics doesn’t exist on its own. You make a great pitch and you sell well.

Visualization 98

Visualization Reporting Metadata Enterprise 98

Ontotext

JUNE 22, 2023

Target discovery also involves a lot of collaboration between researchers and technical teams (data scientists, computational biologists, etc.). Researchers have to sift through huge amounts of data, dispersed over multiple databases as well. We use these data sources to normalize the data we find in research articles.

Metrics 52

Metrics Statistics Visualization Metadata 52

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. That data is never as stable as we’d like to think.

Management 333

Management Machine Learning Experimentation Metrics 333

AWS Big Data

JUNE 6, 2023

What was essential to the solution development was a good understanding of the nature of the data, the source of it (export from GA) as well as the form and scope of the data useful to the data consumers. Business context At SumUp we use GA and Firebase as our digital analytics solutions and AWS as our main Cloud Provider.

Analytics 55

Analytics Data Lake Testing Optimization 55

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. How is data analytics used in the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

erwin

FEBRUARY 4, 2021

While acknowledging that data governance is about more than risk management and regulatory compliance may indicate that companies are more confident in their data, the data governance practice is nonetheless growing in complexity because of more: Data to handle, much of it unstructured. Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

IBM Big Data Hub

JANUARY 17, 2023

These new technologies and approaches, along with the desire to reduce data duplication and complex ETL pipelines, have resulted in a new architectural data platform approach known as the data lakehouse – offering the flexibility of a data lake with the performance and structure of a data warehouse.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

DataKitchen

OCTOBER 11, 2021

The final step is designing a data solution and its implementation. The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes.

Testing 152

Testing Metadata Dashboards Statistics 152

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. There are multiple tables related to customers and order data in the RDS database.

Metadata 121

Metadata Visualization Data Lake Data-driven 121

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. DataBrew is an excellent tool for data quality and preprocessing. For Matching conditions , choose Match all conditions.

Metadata 84

Metadata Sales Data Lake Big Data 84

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. You need to process this to make it ready for analysis.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. A data fabric and data mesh can co-exist.

Management 80

Management Metadata Data Architecture Data Lake 80

Smart Data Collective

SEPTEMBER 26, 2021

Working with massive structured and unstructured data sets can turn out to be complicated. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. So, let’s have a close look at some of the best strategies to work with large data sets. Summarize and sample your data at query time.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

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 110

Data Lake Unstructured Data Data Warehouse Data Quality 110

Cloudera

AUGUST 4, 2021

With hackers now working overtime to expose business data or implant ransomware processes, data security is largely IT managers’ top priority. And if data security tops IT concerns, data governance should be their second priority. Effective data governance must extend beyond the IT organization.

Data Governance 87

Data Governance Metadata Data-driven Enterprise 87

IBM Big Data Hub

OCTOBER 12, 2023

Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc. They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

Ontotext

FEBRUARY 26, 2024

The goal: a data-driven organization Let’s zoom out for a bit. Every organization wants to be data-driven. The goal is to capture data, convert it into the right insights, and integrate those insights quickly and efficiently into your business decisions and processes. Becoming data-driven will also be slow and costly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. Why did Orca choose Apache Iceberg?

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

AWS Big Data

JUNE 12, 2023

Organizations across the world are increasingly relying on streaming data, and there is a growing need for real-time data analytics, considering the growing velocity and volume of data being collected. Next, an AWS Glue streaming ETL (extract, transform, and load) job is set up to process the incoming data.

Management 80

Management Metadata Testing Internet of Things 80

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 76

Cost-Benefit Metadata Optimization Management 76

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. How do business leaders navigate this new data and AI ecosystem and make their company a data-driven organization? The solution is a data fabric. Data integration. Start a trial.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56