data architecture

Companies are investing in data warehouse modernization and data lake projects for descriptive and advanced analytics; however, for the analysis to be holistic, today’s architects weave disparate data streams together, not only from these analytical sources, but also from operational, third party, and streaming data sources. Logical data warehouse is a modern architectural methodology that virtually combines all the data across the enterprise and makes it available to analytical and visualization tools that facilitate timely, insightful, and impactful decisions throughout the enterprise.In...

Self-service is a major goal of modern data strategists. A successfully implemented self-service initiative means that business users have access to holistic and consistent views of data regardless of its location, source or type. As data unification and data collaboration become key critical success factors for organisations, data catalogs play a key role as the perfect companion for a virtual layer to fully empower those self-service initiatives and build a self-service data marketplace requiring minimal IT intervention.Denodo’s Data Catalog is a key piece in Denodo’s portfolio to bridge...

La agilidad como punto clave

What is Data Virtualization and why do I care? In this webinar we intend to help you understand not only what Data Virtualization is but why it's a critical component of any organization's data fabric and how it fits. How data virtualization liberates and empowers your business users via data discovery, data wrangling to generation of reusable reporting objects and data services. Digital transformation demands that we empower all consumers of data within the organization, it also demands agility too. Data Virtualization gives you meaningful access to information that can be shared by a myriad...

In a world where machine learning and artificial intelligence are changing our everyday lives, digital transformation tops the strategic agenda in many private and government organizations. Data is becoming the lifeblood of a company, flowing seamlessly through it to enable deep business insights, create new opportunities, and optimize operations.Chief Data Officers and Data Architects are under continuous pressure to find the best ways to manage the overwhelming volumes of the data that tend to become more and more distributed and diverse.Moving data physically to a single location for...

In un’era sempre più dominata dal cloud computing, dall’AI e dall’analisi avanzata, può sembrare per lo meno anacronistico che molte organizzazioni facciano ancora affidamento ad architetture di dati costruite prima della fine del secolo.Fortunatamente questo scenario sta subendo un cambiamento repentino con l’adozione di nuove tecnologie di integrazione dati, come la virtualizzazione dei dati, che forniscono un livello logico, in tempo reale e sicuro di accesso ai dati aziendali. Le diverse sorgenti dati non devono più essere trasferite fisicamente in un nuovo repositorio e trasformate, ...

Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. For these projects to be successful, data scientists, business analysts, and other personnel need access to data from across the enterprise. However, gaining access to all of the data in an integrated central repository has been a challenge, resulting in up to 80% of the project time being spent on data acquisition and preparation tasks.Data virtualization enables many organizations today to gain data insights from multiple, distributed data sources...

Self service is a major goal of modern data strategists. Denodo’s data catalog is a key piece in Denodo’s portfolio to bridge the gap between the technical data infrastructure and business users. It provides documentation, search, governance and collaboration capabilities, and data exploration wizards. It’s the perfect companion for a virtual layer to fully empower those self service initiatives with minimal IT intervention. It provides business users with the tool to generate their own insights with proper security, governance and guardrails.In this session we will see:The role of a virtual...

Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spend most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.Attend this session to learn how companies can use data virtualization to:Create a logical...

Data is an insurer’s most valuable asset. Capitalizing on all of that stored and incoming data to draw valuable insights for business decisions is what ultimately makes a competitive difference.But, insurers face challenges when it comes to modernizing and digitizing their data architectures. Most organizations rely on traditional systems and data integration processes that are time consuming and slow. In addition, as many adopt cloud strategies, these traditional approaches fill the cloud modernization process with downtime and end user frustration.This is why insurers need a flexible and...