Published By: Attunity
Published Date: Feb 12, 2019
This technical whitepaper by Radiant Advisors covers key findings from their work with a network of Fortune 1000 companies and clients from various industries. It assesses the major trends and tips to gain access to and optimize data streaming for more valuable insights.
Read this report to learn from real-world successes in modern data integration, and better understand how to maximize the use of streaming data. You will also learn about the value of populating a cloud data lake with streaming operational data, leveraging database replication, automation and other key modern data integration techniques.
Download this whitepaper today for about the latest approaches on modern data integration and streaming data technologies.
Published By: IBM APAC
Published Date: May 14, 2019
If anything is certain about the future, it’s that there will be more complexity, more data to manage and greater pressure to deliver instantly. The hardware you buy should meet today’s expectations and prepare you for whatever comes next.
Power Systems are built for the most demanding, data-intensive, computing on earth. Our cloudready servers help you unleash insight from your data pipeline — from managing mission-critical data, to managing your operational data stores and data lakes, to delivering the best server for cognitive computing.
With industry leading reliability and security, our infrastructure is designed to crush the most data-intensive workloads imaginable, while keeping your business protected.
- Simplified Multicloud
- Built-in end-to-end security
- Proven Reliability
- Industry-leading value and performance
Power Systems are built for the most demanding, data-intensive, computing
on earth. Our cloud-ready servers help you unleash insight from your
data pipeline—from managing mission-critical data, to managing your
operational data stores and data lakes, to delivering the best server for
We’ve heard it before. A data warehouse is a place for formally-structured, highly-curated data, accommodating recurring business analyses, whereas data lakes are places for “raw” data, serving analytic workloads, experimental in nature. Since both conventional and experimental analysis is important in this data-driven era, we’re left with separate repositories, siloed data, and bifurcated skill sets.
Or are we? In fact, less structured data can go into your warehouse, and since today’s data warehouses can leverage the same distributed file systems and cloud storage layers that host data lakes, the warehouse/lake distinction’s very premise is rapidly diminishing. In reality, business drivers and business outcomes demand that we abandon the false dichotomy and unify our data, our governance, our analysis, and our technology teams.
Want to get this right? Then join us for a free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and special guest, Dav
Traditional databases and data warehouses are evolving to capture new data types and spread their capabilities in a hybrid cloud architecture, allowing business users to get the same results regardless of where the data resides.
The details of the underlying infrastructure become invisible. Self-managing data lakes automate the provisioning, reliability, performance and cost, enabling data access and experimentation.
Analyst firm, Enterprise Strategy Group, examines how companies can leverage cloud-based data lakes and self-service analytics for timely business insights that weren’t possible until now.
And learn how IBM Cloud Object Storage, as a persistent storage layer, powers analytics and business intelligence solutions on the IBM Cloud.
Complete the form to download the analyst paper.
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