Mon.Mar 29, 2021

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Big Data Trends That Are Disrupting Management Maintenance

Smart Data Collective

Big data is leading to some major breakthroughs in the modern workplace. One study from NewVantage found that 97% of respondents said that their company was investing heavily in big data and AI. Maintenance management’s primary focus has always been maximizing the quality, effectiveness, and quality of equipment in an organization. And this is usually at the lowest possible costs in terms of material and machinery.

Big Data 136
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Improving Collaboration with a DataOps Platform

DataKitchen

The post Improving Collaboration with a DataOps Platform first appeared on DataKitchen.

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Are You Getting The Most Out Of Your Marketing Data?

Smart Data Collective

These are unprecedented times for the analytics industry. Thanks to new tools, including real-time tracking capabilities, businesses had access to more information about their marketing campaigns than ever before. That’s good news, right? Well, it should be, but having access to more marketing data is only actually good news when businesses understand what to do with it.

Marketing 121
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RDF-star Implementation in GraphDB and How Synaptica Used It Within Graphite for Access Control

Ontotext

Ontotext: What is RDF-star? Vassil Momtchev: RDF-star (formerly known as RDF*) helps in every case, where the user needs to express a complex relationship with metadata associated for a triple like: 1. << :man :hasSpouse :woman >> 2. :source :TheNationalEnquirer ; 3. : webpage <[link] 4. : retrieved "2020-02-13"^^ xsd:dateTime. Technically speaking, RDF-star is the syntactic sugar, which makes it easier to attach metadata to edges in the graph.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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5 Tips to Making Data Prep More Efficient in Dataiku

Dataiku

With more use cases to untap, more data science projects in the queue, and more performance metrics to hit, data science teams (and their broader counterparts throughout the business) are under a lot of pressure to decrease the amount of time it takes for them to do things like data prep and maximize productivity. Here, we provide five easy ways that Dataiku users can do just that, in order to ultimately spend more time on the high-value parts of the project.

Metrics 59
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Data Fabrics Need to Coexist with Data Warehouses and Other Database-Centric Technologies

Data Virtualization

Since the dawn of IT, business was in need of one integrated, consistent view of the data coming in from multiple applications, and for a long time, data warehouses have been the preferred choice to solve this problem. Recently, data. The post Data Fabrics Need to Coexist with Data Warehouses and Other Database-Centric Technologies appeared first on Data Virtualization blog.

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Data Fabrics Need to Coexist with Data Warehouses and Other Database-Centric Technologies

Data Virtualization

Since the dawn of IT, business was in need of one integrated, consistent view of the data coming in from multiple applications, and for a long time, data warehouses have been the preferred choice to solve this problem. Recently, data.

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On-Demand Spark clusters with GPU acceleration

Domino Data Lab

Apache Spark has become the de-facto standard for processing large amounts of stationary and streaming data in a distributed fashion. The addition of the MLlib library, consisting of common learning algorithms and utilities, opened up Spark for a wide range of machine learning tasks and paved the way for running complex machine learning workflows on top of Apache Spark clusters.

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Data Catalogs for Search & Discovery

Alation

How data catalogs with search & discovery help users. Staying ahead in business is challenging — but essential. Every business feels the pressure of competition, resource scarcity, and disruption due to technology breakthroughs. To keep up, more businesses have shifted toward data-driven decision making. According to a NewVantage Partners Report , 96% of executives indicate that their organization aspires to a data-driven culture, while only 24% report success.

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Accelerated integration of Eventador with Cloudera – SQL Stream Builder

Cloudera

In October 2020, Cloudera made a strategic acquisition of a company called Eventador. This was primarily to augment our streaming capabilities within Cloudera DataFlow. Eventador was adept at simplifying the process of building streaming applications. Their flagship product, SQL Stream Builder, made access to real-time data streams easily possible with just SQL (Structured Query Language).

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.