Cloudera

FEBRUARY 14, 2018

I’ve spent the last four years here at Cloudera talking with our customers about how to run their businesses better using their data and Cloudera’s products and services. Now I get to put my money where my mouth is – and turn my focus internally on how we at Cloudera can become more data-driven. The first is visibility.

Data-driven 44

Data-driven Data Quality Risk Interactive 44

Laminar Security

DECEMBER 13, 2023

In the ever-evolving digital landscape, the importance of data discovery and classification can’t be overstated. As we generate and interact with unprecedented volumes of data, the task of accurately identifying, categorizing, and utilizing this information becomes increasingly difficult.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

Data Governance 76

Data Governance Business Objectives Data Quality Strategy 76

AWS Big Data

APRIL 4, 2024

Many enterprises are migrating their on-premises data stores to the AWS Cloud. During data migration, a key requirement is to validate all the data that has been moved from source to target. This data validation is a critical step, and if not done correctly, may result in the failure of the entire project.

Data Quality 62

Data Quality Data Lake Data Warehouse Data-driven 62

IBM Big Data Hub

NOVEMBER 28, 2022

Metadata management performs a critical role within the modern data management stack. It helps blur data silos, and empowers data and analytics teams to better understand the context and quality of data. This, in turn, builds trust in data and the decision-making to follow. Improve data discovery.

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

datapine

JANUARY 24, 2021

In our cutthroat digital age, the importance of setting the right data analysis questions can define the overall success of a business. That being said, it seems like we’re in the midst of a data analysis crisis. Your Chance: Want to perform advanced data analysis with a few clicks? Data Is Only As Good As The Questions You Ask.

IT 317

IT Statistics KPI Data-driven 317

Alation

AUGUST 9, 2022

Today, data is more valuable to a company than it’s ever been. It can help you make data-driven decisions which can improve business performance, boost revenue, and improve efficiencies. But in the four years since it came into force, have companies reached their full potential for data integrity? What is data integrity?

Data Integration 52

Data Integration Data Quality Measurement Strategy 52

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? So it’s Monday, and you lead a data analytics team of perhaps 30 people. And she is numbers driven – great! Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. What should be in that report about your data team?

Metrics 130

Metrics Data Analytics Analytics Measurement 130

AWS Big Data

APRIL 19, 2023

Data mesh is a new approach to data management. Companies across industries are using a data mesh to decentralize data management to improve data agility and get value from data. This is especially true in a large enterprise with thousands of data products.

Technology 82

Technology Data-driven Machine Learning Sales 82

Ontotext

APRIL 10, 2024

The data ecosystem today is crowded with dazzling buzzwords, all fighting for investment dollars. A survey in 2021 found that a data company was being funded every 45 minutes. Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

CIO Business Intelligence

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making.

Data Strategy 110

Data Strategy Strategy Machine Learning Data-driven 110

IBM Big Data Hub

JANUARY 25, 2023

In our last blog , we introduced Data Governance: what it is and why it is so important. Organizations have long struggled with data management and understanding data in a complex and ever-growing data landscape. Silos exist naturally when data is managed by multiple operational systems.

Data Governance 52

Data Governance Data-driven Strategy Management 52

Ontotext

JANUARY 29, 2024

In 2023, data leaders and enthusiasts were enamored of — and often distracted by — initiatives such as generative AI and cloud migration. I expect to see the following data and knowledge management trends emerge in 2024. However, organizations need to be aware that these may be nothing more than bolted-on Band-Aids.

Strategy 52

Strategy Management Metadata Data-driven 52

Ontotext

JUNE 10, 2021

And yeah, the real-world relationships among the entities represented in the data had to be fudged a bit to fit in the counterintuitive model of tabular data, but, in trade, you get reliability and speed. Ironically, relational databases only imply relationships between data points by whatever row or column they exist in.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

Cloudera

SEPTEMBER 15, 2022

Cloudera Contributor: Mark Ramsey, PhD ~ Globally Recognized Chief Data Officer. July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. Luke: What is a modern data platform?

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

IBM Big Data Hub

NOVEMBER 24, 2023

Application modernization starts with assessment of current legacy applications, data and infrastructure and applying the right modernization strategy (rehost, re-platform, refactor or rebuild) to achieve the desired result. Duplicative capabilities across applications and channels give rise to duplicative IT resources (e.g.,

Cost-Benefit 89

Cost-Benefit Testing Data-driven Enterprise 89

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Sisense

AUGUST 28, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. What is data integrity? Data integrity risks.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 82

Data Lake Data Governance Data Architecture Data Warehouse 82

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) Agreeing on metrics.

Marketing 363

Marketing Experimentation Metrics Testing 363

Ontotext

JANUARY 26, 2023

In today’s world, we increasingly interact with the environment around us through data. This might include a range of tasks such as searching weather conditions on an app, looking at the temperature at home, reviewing electricity usage on a dedicated web platform, all the way to managing and utilizing data in a professional system at work.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 75

Data Quality Data Lake Data-driven Metrics 75

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 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

erwin

JUNE 11, 2020

What Is Data Intelligence? Data Intelligence is the analysis of multifaceted data to be used by companies to improve products and services offered and better support investments and business strategies in place. Data intelligence can encompass both internal and external business data and information. Healthcare.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

Smart Data Collective

APRIL 29, 2020

As the world is gradually becoming more dependent on data, the services, tools and infrastructure are all the more important for businesses in every sector. Data management has become a fundamental business concern, and especially for businesses that are going through a digital transformation. What is data management?

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

datapine

MARCH 27, 2019

We’re living in the midst of the age of information, a time when online data analysis can determine the direction and cement the success of a business or a startup that decides to dig deeper into consumer behavior insights. By managing customer data the right way, you stand to reap incredible rewards.

Management 129

Management Data-driven Dashboards Visualization 129

Laminar Security

DECEMBER 1, 2023

Cloud data security is one of the most critical, yet most challenging aspects of doing business in the age of cloud. As more organizations migrate their data to the cloud, they face an increasing range of risks and threats, including data breaches, data leakage, data loss, data misuse, data compliance violations, shadow data and more.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. The power of the data lake lies in the fact that it often is a cost-effective way to store data.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

Alation

JULY 19, 2021

Metadata is information about data. Folks who work closely with data, like analysts, data scientists, and IT teams, rely on metadata to give them crucial context for how to use a given asset. Today, metadata is extremely helpful in classifying, describing, and providing critical information about digital data.

Metadata 105

Metadata Management Data Governance Machine Learning 105

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

BI-Survey

AUGUST 1, 2019

Data is a central resource in the 21st century. Only those who manage to extract value from their data will remain competitive. For this reason, many organizations are looking at innovative ways of using their data to create value. Data products (i.e., Data monetization is at an early stage of adoption but is expanding.

Cost-Benefit 53

Cost-Benefit Data Quality Reporting Data-driven 53

FineReport

APRIL 26, 2023

As the world becomes increasingly digitized, the amount of data being generated on a daily basis is growing at an unprecedented rate. This has led to the emergence of the field of Big Data, which refers to the collection, processing, and analysis of vast amounts of data. What is Big Data? What is Big Data?

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. There are four groups of data that are naturally siloed: Structured data (e.g., Transaction and pricing data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 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. Why AI software development is different.

Management 339

Management Machine Learning Experimentation Metrics 339

DataRobot Blog

MARCH 10, 2022

These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. This type of growth has stressed legacy data management systems and makes it nearly impossible to implement a profitable data-centered solution. High-level example of a common machine learning lifecycle.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

O'Reilly on Data

OCTOBER 22, 2020

Understanding the company’s true purpose unlocks the business model and sheds light on what is useful to do with the data. Since I work in the AI space, people sometimes have a preconceived notion that I’ll only talk about data and models. How did you obtain your training data? Source: Shane.

Consulting 303

Consulting Risk Cost-Benefit Modeling 303