Creating a Big Data Platform Roadmap

Perficient Data & Analytics

One of the most frequently asked questions by our customers is the roadmap to deploying a Big Data Platform and becoming a truly data-driven enterprise. Just as you can’t build a house without a foundation, you can’t start down a big data path without first establishing groundwork for success. There are several key steps to prepare the organization to realize the benefits of a big data solution with both structured and unstructured data.

Fact or Fiction? Smart Data Visualization Tells the Tale

Smarten

If you are considering a Business Intelligence solution, you ought to give some consideration to the concept of Smart Data Visualization and review your prospective solution to determine its capabilities in that regard. How do users perceive and use data?

Big Data Ingestion: Parameters, Challenges, and Best Practices

datapine

Businesses are going through a major change where business operations are becoming predominantly data-intensive. quintillions of bytes of data are being created each day. This pace suggests that 90% of the data in the world is generated over the past two years alone. Big Data.

Introduction To The Basic Business Intelligence Concepts

datapine

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. Your fast thinking system can take in massive amounts of data at once. They prevent you from drowning in data. The data warehouse.

Research quality data and research quality databases

Simply Statistics

When you are doing data science, you are doing research. You want to use data to answer a question, identify a new pattern, improve a current product, or come up with a new product. That is why the key word in data science is not data, it is science.

Key Differences between a Traditional Data Warehouse and Big Data

Perficient Data & Analytics

Traditional data warehouse solutions were originally developed out of necessity. The data captured from these traditional data sources is stored in relational databases comprised of tables with rows and columns and is known as structured data. So how do you make the data gathered more useful? This process begins with data consolidation tools like Informatica or Oracle Data Integrator. What is Big Data? Multi-Structured Data.

Data Lakes on Cloud & it’s Usage in Healthcare

BizAcuity

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. Deploying Data Lakes in the cloud.

Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics). pattern detection and pattern recognition in data). NLG is a software process that transforms structured data into human-language content.

Okay, You Got a Knowledge Graph Built with Semantic Technology… And Now What?

Ontotext

Whether you refer to the use of semantic technology as Linked Data technology or smart data management technology, these concepts boil down to connectivity. Connectivity in the sense of connecting data from different sources and assigning these data additional machine-readable meaning.

Test principles – Data Warehouse vs Data Lake vs Data Vault

Perficient Data & Analytics

Understand Data Warehouse, Data Lake and Data Vault and their specific test principles. This blog tries to throw light on the terminologies data warehouse, data lake and data vault. Let us begin with data warehouse. What is Data Warehouse?

AML: Past, Present and Future – Part III

Cloudera

The system must: Ingest, process, analyze, store, and serve all types of AML data, be it structured (database tables), unstructured (contracts, e-mails, etc.), Handle increases in data volume gracefully. Provide audit and data lineage information to facilitate regulatory reviews.

Themes and Conferences per Pacoid, Episode 7

Domino Data Lab

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! Evolving Data Infrastructure: Tools and Best Practices for Advanced Analytics and AI (Jan 2019).

Why CU Anschutz Medical Campus Migrated to Google Cloud

Perficient Data & Analytics

Our healthcare team has been working with the University of Colorado over the past couple of years to overcome critical data challenges in healthcare… and the results are exciting. On-premises data warehouse was costly and non-scalable. Integrating vast amounts of clinical data.

How You Can Get Proactive About Margin Leaks Using the Pocket Price Waterfall

The Kini Group

This visualization helps keeps sales teams accountable for their deal-closing tactics. Individual revenue-damaging issues: Data averages don’t show the full picture. The framework therefore increases pricing discipline with data-driven approach. Align your data and access to it.

Sales 68