Data + Intelligence

Informatica Intelligent Cloud Services (IICS) now offers a free command line utility that can be used to integrate your ETL jobs into most enterprise release management pipelines. It’s called the Asset Management command line interface (CLI). Version two now allows you to extract an IICS job into a single compressed file. Moving a single standalone […]

The storage of unstructured data is on the rise in modern data warehouses due to the increasing collection of text data and metadata in an unstructured format. Like most data warehousing solutions, Snowflake offers support to load and manipulate semi-structured files and data. This is essential, as, modern data warehousing systems need to store large […]

Our worldwide pandemic has hit everyone differently. Even within the same circles, people are handling and responding to these changes in different ways. I have found such strength and inspiration from the IT industry and our clients. Everyone has approached this challenge head-on. My professional community has provided such a grounding force by facing this […]

What is Databricks? Databricks is a unified cloud-based data platform that is powered by Apache Spark. It specializes in collaboration and analytics for big data. Databricks is a data science workspace, with Collaborative Notebooks, Machine Learning Runtime, and Managed ML flow. Collaborative Notebooks support multiple data analytics languages, such as SQL, Scala, R, Python, and […]

Due to COVID-19, it is critical for healthcare providers to have real-time, unified access to data. With the pandemic pushing this industry to its limits, the need for data interoperability is higher than ever. In order to adapt to these conditions, healthcare organizations need easy-to-use technology to support the exchange of healthcare information. To fill […]

In our first post, we discussed the need to move away from standalone application solution approach to search connectors. In this post, we will describe the Handshake architecture at a high level. We elected to move towards a microservice architecture for a few reasons: Less resource intensive Scheduling, component reuse, and maintenance Newer and growing […]

Introducing Handshake This post is the first in a series on Perficient’s newest product: Handshake, the Extensible Search Connector. Perficient’s Data Solution group has built more than 30 custom search connectors. FileNet P8, Documentum, JIRA/Confluence, Salesforce, and Adobe Experience Manager to name a few. As more customers recognize the benefits of search, the demand for […]

Health insurance providers are moving swiftly as part of the COVID-19 solution From the beginning of the COVID-19 pandemic, health insurance providers have made decisive steps to help patients, support healthcare providers, and curb the spread of the virus. The need is significant, particularly as healthcare providers lose important revenue streams in order to prioritize […]

Perficient’s Managing Director and Chief AI Strategist Christine Livingston recently joined IBM’s Big Data and Analytics team on its Making Data Simple podcast series. In this episode, AI adoption practices for the enterprise, Christine talks about her approach to AI within the consulting and enterprise industries, along with how she and her team have been […]

Cloud can create tremendous advantages by helping you harness data-driven insight, but many enterprises are still faced with a significant legacy system presence. Many companies find that the basic cloud model doesn’t address transformation complexities such as skills gaps, compliance, integration issues, vendor lock-in, and more. That’s why IBM has designed Cloud Pak for Data […]

Frequently, the “crawl, walk, run, fly” metaphor is used when describing the path to implementing a scalable data science practice. There are a lot of problems with this concept, not the least of which is the fact there is already motion involved. People are already doing BI work, often complex work enabling high value results. […]

Tuning Spark for your machine learning pipeline can be a complex and time consuming process. Store and compute play a different role for your Spark cluster in different stages of your machine learning pipeline. Spark defaults are never the right way to go. It makes more sense to know what settings are most effective at […]