A collection of big data white papers reviewed by the editors of insideBIGDATA. Please visit the insideBIGDATA White Paper Library for a comprehensive list of white papers focus on big data strategies.

How big data works? How we use it at FunCorp, and why it’s one of our most important tools

The latest report on big data from FunCorp discusses how an increased usage in smartphone users has also led to a rising demand for better mobile apps. These modern apps also use tremendous amounts of data, and thus, a robust management tool for analyzing and managing this data has become a necessity. This is where the use of Big Data comes in (this includes FunCorp too). The company develops apps and has relied heavily on big data. Read this report to learn how.

Be (More) Wrong Faster – Dumbing Down Artificial Intelligence with Bad Data

In this white paper,”Be (More) Wrong Faster – Dumbing Down Artificial Intelligence with Bad Data,” our friends over at Profisee discuss how Master Data Management (MDM) will put your organization on the fast track to automating processes and decisions while minimizing resource requirements, while simultaneously eliminating the risks associated with feeding AI and ML data that is not fully trusted. In turn, your digital business transformation will be accelerated and your competitive edge will be rock solid.

The Real AI Revolution: Machines That Learn Like Scientists

In this compelling white paper, our friends over at causaLens highlight how ML has wrongly become synonymous with AI. We must shake off this misconception to start the real AI revolution. Data science must forgo its reliance on curve-fitting ML and return to its roots; to put the science back into data science. A growing number of leading scientists – from Turing Award winning Professors Judea Pearl and Yoshua Bengio, to Professor Bernhard Schölkopf, Director of Germany’s Max Planck Institute for Intelligent Systems – are advocating for the development of a new science of causality, that goes far beyond statistical pattern matching.

The State of Data Management – Why Data Warehouse Projects Fail

Based on new research commissioned by SnapLogic and conducted by Vanson Bourne, who surveyed 500 IT Decision Makers (ITDMs) at medium and large enterprises across the US and UK, this whitepaper explores the data management challenges organizations are facing, the vital role data warehouses play, and the road to success.

Big Data Performance Report

To shed light on how IT operations teams are dealing with working in challenging environments, Pepperdata has carried out a period of customer research. This report revealed a wealth of insights regarding the condition of enterprise workloads that lack the benefits of observability and continuous tuning. Combined with cloud computing statistics and a more general understanding of big data industry trends, there is much to learn here about the present and future of the data analytics industry.

The Impact of Data Science On Customer Intelligence, Space Strategy and Supply Chain Optimization

In a new white paper recently released, “The Impact of Data Science On Customer Intelligence, Space Strategy and Supply Chain Optimization”, 84.51° explains how this innovative data science has become embedded- specifically in three of its missions: Customer Intelligence, Space Strategy and Supply Chain Optimization.

A Comprehensive Guide to Evaluating Customer Data Platforms (CDPs)

This white paper by our friends over at HGS Digital aims to help you evaluate Customer Data Platform (CDP) vendors on various key areas. Investing in a CDP should be done with a long-term aim – various systems from which the data is imported and systems to which data is exported may change over time, but the CDP becomes the master repository of data and should be leveraged by the marketing organization for a very long time.

Special Report: The State of AI and Machine Learning

Appen Limited, a leading provider of high-quality training data for organizations that build effective AI systems at scale, released its annual State of AI Report for 2020. The report highlights increasing C-suite involvement and investment in enterprise AI projects as well as data being a key challenge as AI models get more frequent updates in production. The report also reveals the recent acceleration of AI strategies in the wake of the COVID-19 pandemic.

The Future Starts Now – Achieving Successful Operation of ML & AI-Driven Applications

Operationalizing AI and ML has become an unavoidable need in business, as various industries heavily rely on large volumes of real-time data as input to automated decision-making processes to yield the best results. Use cases in the data science field have shown that ML models and AI have few tangible business benefits until they are operationalized. In this e-book, our friends over at MemSQL show us how to successfully deploy model-driven applications into production.

Building Powerful Enterprise AI Infrastructure: How to Design Enduring Infrastructure for AI

Our friends over at cloud-neutral colocation data center company Interxion have published a whitepaper titled, “Building Powerful Enterprise AI Infrastructure: How to design enduring infrastructure for AI,” which details the requirements of an ideal infrastructure environment when it comes to reaping the benefits of today’s growing volume of data and enabling AI at scale. By automating repetitive processes, delivering new strategic insights, and accelerating innovation, AI has the power to revolutionize business.