Overview

Integrated Delivery networks (IDNs) face complex challenges in getting the right data into the right hands, at the right time, with the goal of more informed decision-making and improved clinical and financial performance.

How do you balance the need to achieve an early success with SOA against the requirement for an architecture that will deliver long term success? You don't want to get bogged down in architectural committees for three years, but you don't want to make short term decisions that will be roadblocks to long term success.

Executive Overview

One way financial services firms can improve their operational efficiency is to revamp their data management infrastructure. Creating a central repository for data that is used by multiple applications can ensure data consistency and quality across the enterprise, ease integration bottlenecks, and lower the number of failed trades.However, different applications have different database usage patterns. To satisfy them all, any central data repository must:

Are you new to Ensemble? InterSystems provides several tools to learn the basics of Ensemble and get on your way to becoming an expert in the technology. Before installing Ensemble, take a look at the Ensemble Technology Overview and Getting Started with Ensemble in documentation. Respectively, these documents explain features and major components of Ensemble as well as how to install the software.

Introduction

With the growing popularity of smart phones and tablet computers, consumers are coming to expect that software solutions will be presented as "apps" on their mobile devices. The challenge for most application developers is to find ways to make their existing solutions run on modern mobile platforms without incurring the delay and cost of a complete rewrite.

Introduction

In healthcare, information accessibility can impact the outcome of a medical decision, or the success of a bundled payment initiative. To ensure that the right information is available at the right place and time, healthcare organizations typically have used HL7® interface engines to share data among clinical applications. But the demands on healthcare information technology are changing so rapidly that these simple engines are no longer sufficient.

Introduction

Executive Overview

Executive Summary

The best way to compare the performance of database products is in a head-to-head test using a real application, preferably one of your own. This is especially true when evaluating Caché's post-relational technology, because "standard" transaction processing benchmarking methodologies assume the restrictive "row and columns" format of a relational database. They cannot accurately predict the performance of real applications, which often use complex data models.

Introduction - Analyzing Textual Big Data

Big Data for Enriching Analytical Capabilities - Big data is revolutionizing the world of business intelligence and analytics. Gartner predicts that big data will drive $232 billion in spending through 2016, Wikibon claims that by 2017 big data revenue will have grown to $47.8 billion, and McKinsey Global Institute indicates that big data has the potential to increase the value of the US health care industry by $300 billion and to increase the industry value of Europe's public sector administration by Ä250 billion.

Abstract

A benchmark of a real-world application, which loads data into a data warehouse for subsequent analysis, was performed. To conduct the benchmark, one module of the Oracle-based application was replicated in Caché ObjectScript. Only about 40 person-hours of work was required to duplicate the functionality of the original module in Caché.

Introduction

Australia's recent launch of the Personally Controlled Electronic Health Record (PCEHR) - a significant step towards establishing a national e-Health infrastructure - has simultaneously provided a boost to shared Electronic Patient Record (EPR) projects and delivered a wake-up call to healthcare providers about their readiness for connected care initiatives. In countries around the world, the era of connected care is here.

Introduction

Impedance mismatch is a term commonly used to describe the problem of an object-oriented (OO) application housing its data in legacy relational databases (RDBMS). C++ programmers have dealt with it for years, and it is now a familiar problem to Java and other OO programmers.

Introduction

This document is intended to provide a survey of various High Availability (HA) strategies that can be used in conjunction with InterSystems Caché, Ensemble, and HealthShare Foundation. This document also provides an overview of the various types of system outages that can occur, as well as how each strategy would handle a given outage, with the goal of helping you choose the right strategy for your specific deployment.

The strategies surveyed in this document are based on three different HA technologies: