Texas Rangers data transformation modernizes stadium operations

CIO

The old stadium, which opened in 1992, provided the business operations team with data, but that data came from disparate sources, many of which were not consistently updated. We knew we were going to have tons of new data sources,” Noel says. Analytics, Data Management

Data Transformation: Standardization vs Normalization

KDnuggets

Increasing accuracy in your models is often obtained through the first steps of data transformations. This guide explains the difference between the key feature scaling methods of standardization and normalization, and demonstrates when and how to apply each approach.

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‘Phase Two’ of Europe’s Data Transformation

Corinium

For the UK and Europe’s most data-led companies, phase one of the data transformation is now complete. Data StrategyThe strategies have been agreed, the foundations have been laid and the real work is well underway.

‘Phase Two’ of Europe’s Data Transformation

Corinium

For the UK and Europe’s most data-led companies, phase one of the data transformation is now complete. Data StrategyThe strategies have been agreed, the foundations have been laid and the real work is well underway.

4 Key Steps to Data Transformation Success with Data Mesh

It’s tougher than ever to give your clients the data and insight they need, when they need it (and how they want it) – while addressing issues like security. Find out how data mesh architectures can help you meet these challenges and more.

The Automated Approach to Ensuring Data Privacy and Hygiene – Smart Data Transformation Solutions

DataFloq

From likes to shares, tweets to swipes, data is being generated at a break-neck speed—oozing out of the devices we use every day, it shows no sign of slowing down. The digital world is exploding with massive volumes of data that are predominantly unstructured.

What companies get wrong about data transformation

CIO Business Intelligence

For years, IT and data leaders have been striving to help their companies become more data driven. But technology investment alone is not enough to make your organization data driven. According to Alation, companies that have a strong data culture outperform their peers.

Why You Should Prioritize Data Transformation Above Other Digital Transformation Initiatives

DataFloq

Chance are you’re aiming to invest in a BI and analytics program to capitalize on the big data your company has been acquiring over the years. But before you spend millions on opting for expensive BI programs, take a step back and ask yourself three questions:Do I have data I can trust?Do

How Your Finance Team Can Lead Your Enterprise Data Transformation

Alation

Today’s best-performing organizations embrace data for strategic decision-making. Because of the criticality of the data they deal with, we think that finance teams should lead the enterprise adoption of data and analytics solutions. Start Today with the Alation Data Catalog.

Data Transformation: How to Transform Data More Efficiently

Dataiku

Wouldn’t it be great if data just came to you ready and primed for analysis? Unfortunately, as data often comes from different sources, with different definitions, and without standardization, it nearly always requires some modification to be useful for its target destination.

Insights, trends, and best practices in driving data transformation, upskilling, and building data cultures

DataCamp

We’ve compiled a list of resources to inform your data transformation, data culture initiative, and data upskilling. Explore these webinars and white papers

5 Questions every CEO should ask before embarking on a Data Transformation

Peter James Thomas

But the 5 questions I highlight are as follows: Why does my organisation need to embark on a Data Transformation – what will it achieve for us? Do I have the expertise and experience on hand to scope a Data Transformation and then deliver it? How long will a Data Transformation take and how much will it cost? Is there an end state to our Data Transformation, or do we need a culture of continuous data improvement?

Accelerating Digital And Data Transformation In A Remote-Work World

Bruno Aziza

Leading companies are undertaking a wholesale transformation to enable remote work leveraging digital capabilities and data. Innovation /innovation cionetwork technology

Data Engineering – A Journal with Pragmatic Blueprint

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Data Engineering In recent days the consignment of data produced from innumerable sources is drastically increasing day-to-day.

Is Big Data Transforming Our Broken Hospital Management Systems?

Smart Data Collective

The healthcare industry is happily embracing big data. Hospitals around the world are finding that data can have a profound impact on their operations. A lot of the emphasis so far has been on the use of big data to better engage with external third-parties, but big data can be equally valuable for managing internal hospital systems. Big Data is the Key to Improving the Efficiency of Hospital Management Systems? Big Data is the Key to Hospital Management.

First-ever IBM Analytics University empowers data transformation

IBM Big Data Hub

If you’re holding an event for the very first time, what helps you gauge its success? At IBM Analytics University, we turned to social media analytics. Here’s a summary of what we learned from the experts and from Watson Analytics for Social Media

GroupBy in Pandas: Your Guide to Summarizing and Aggregating Data in Python

Analytics Vidhya

The post GroupBy in Pandas: Your Guide to Summarizing and Aggregating Data in Python appeared first on Analytics Vidhya. Beginner Data Exploration Python Structured Data Technique aggregation data transformation filtration groupby pandas python split-apply-combine

Feature Transformation and Scaling Techniques to Boost Your Model Performance

Analytics Vidhya

Overview Understand the requirement of feature transformation and training techniques Get to know different feature transformation and scaling techniques including- MinMax Scaler Standard Scaler.

How Compliance And Cost Reduction Are Funding Data Transformation

Bruno Aziza

Although CIO’s and CDO’s aspire to be on the offensive in using data to drive revenue generation and business growth, it is defensive initiatives that are providing cover for forward-looking transformation ambitions

Top-Down vs. Bottom-Up Culture Change

Dataiku

Last year when we surveyed over one hundred data professionals, they ranked organizational change as their third biggest data challenge (behind data cleaning and model productionalization). However, this year, organizational change moved up to the second place slot, suggesting that organizations have not yet overcome the culture change obstacles to data integration. organization Culture Data Transformation

Loading Data in GraphDB: Best Practices and Tools

Ontotext

Data is just the first step on the path towards knowledge. This is good when we are working with data that can be read by multiple tools. If that’s the case with images, imagine how bad it must be for structured data stored in databases. Many data scientists are fans of Python.

How AI is Transforming Banks & Banking

Dataiku

Data has always been the foundation of the banking industry. What has changed in recent years, of course, is the amount of data available and the speed at which it is processed as well as the need to quickly respond to market changes. EnterpriseAI financial services Data Transformation

Start Thinking About DataOps

TDAN

Everyone’s talking about data. Data is the key to unlocking insight— the secret sauce that will help you get predictive, the fuel for business intelligence. The transformative potential in AI? It relies on data. The good news is that data has never […].

The Rising Need for Data Governance in Healthcare

Alation

Healthcare is changing, and it all comes down to data. Data & analytics represents a major opportunity to tackle these challenges. Indeed, many healthcare organizations today are embracing digital transformation and using data to enhance operations. Lab data.

BHP Leverages the Denodo Platform to Create a Logical Data Fabric

Data Virtualization

Business Real Cases Advanced analytics AWS BHP Cloud Data Architecture data driven organization data fabric Data Science Data Sources data strategy data transformation data virtualization Denodo Platform logical data fabric

IT 52

Successful Data Virtualisation: more than the right choice of platform

Data Virtualization

Learn in 12 minutes: What makes a strong use case for data virtualisation How to come up with a solid Proof of Concept How to prepare your organisation for data virtualisation You’ll have read all about data virtualisation and you’ve.

Data Architecture Crash Course: Key Terms

Dataiku

We’ve set out to demystify the jargon surrounding data architecture to enable every team to understand how it impacts their objectives. Hadoop Enterprise Ai Data Transformation data architectureNot sure what Hadoop actually is? A little fuzzy on what the difference is between cloud and on-prem storage?

Steering Clear of Security Breaches: Maintaining Cloud Integrity in 2020

Sirius Computer Solutions

When people hear the term “cloud,” they have some idea of a technology functioning somewhere in space that can store, run and manage data applications. Where will your data actually be stored? Blog Cloud Cloud Security Cybersecurity data transformation Security

Data Preparation and Data Mapping: The Glue Between Data Management and Data Governance to Accelerate Insights and Reduce Risks

erwin

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results. The problem usually starts by relying on manual integration methods for data preparation and mapping. Data Quality Obstacles.

Prevent Rain Clouds Along Your Snowflake Migration

Sirius Computer Solutions

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. However, potential storm clouds can build on the horizon in two key areas: Data migration and ongoing transformation of data. In this post, we focus on data migration and ongoing transformation.

Using Apache Flink with Java

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Apache Flink is a big data framework that allows programmers to process huge amounts of data in a very efficient and scalable way.

AI Maturity Survey: Where Are We in the Path to Enterprise AI?

Dataiku

With all the media hype and coverage around AI, one might think that every company out there has Enterprise AI all figured out and is extremely mature in their data journey. However, we surveyed more than 350 data professionals and found a different story. ai Data Strategy Data Transformation

CDO resumes: 5 tips for landing a chief data officer role

CIO

As companies start to adapt data-first strategies, the role of chief data officer is becoming increasingly important, especially as businesses seek to capitalize on data to gain a competitive advantage. Focus on transformation.

Data is the new ingredient at Everest Ice Cream

Phocas

However to carry out continual improvement and gain efficiencies – Everest sought some extra assistance – in data analytics. The management team turned to the Phocas’ data analytics solution to help them track sales, pinpoint poor performing products and reduce waste.

DataOps Should Be Part of Everyone on the Data Team

DataKitchen

Data Transformers podcast hosts Peggy Tsai & Ramesh Dontha chat with DataKitchen CEO Chris Bergh about how DataOps should be 10% of every data team member's job. The post DataOps Should Be Part of Everyone on the Data Team first appeared on DataKitchen.

From Blob Storage to SQL Database Using Azure Data Factory

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Azure data factory (ADF) is a cloud-based ETL (Extract, Transform, Load) tool and data integration service which allows you to create a data-driven workflow.

An Introductory Guide to Feature Stores | Domino Data Lab

Domino Data Lab

The most efficient way to use them across an organization is in a feature store that automates the data transformations, stores them and makes them available for training and inference. Features are input for machine learning models.

How do Transformers Work in NLP? A Guide to the Latest State-of-the-Art Models

Analytics Vidhya

Overview The Transformer model in NLP has truly changed the way we work with text data Transformer is behind the recent NLP developments, including. The post How do Transformers Work in NLP? NLP Python data science deep learning Natural language processing nlp transformer python transformerA Guide to the Latest State-of-the-Art Models appeared first on Analytics Vidhya.

BMW creates data hub with Amazon to boost efficiency

DataFloq

LONDON (Reuters) - BMW has developed a data hub with Amazon's cloud computing division, in a sign of how companies are increasingly using "big data" to try to boost efficiency. "We We have a few hundred data scientists at BMW, but the aim is to make the data accessible to everyone.".

KDnuggets News, August 17: How to Perform Motion Detection Using Python • The Complete Collection of Data Science Projects

KDnuggets

How to Perform Motion Detection Using Python • The Complete Collection of Data Science Projects - Part 2 • What Does ETL Have to Do with Machine Learning? Data Transformation: Standardization vs Normalization • The Evolution From Artificial Intelligence to Machine Learning to Data Science. KDnuggets 2022 Issues News

What is a Feature Store? | Domino Data Lab

Domino Data Lab

The most efficient way to use them across an organization is in a feature store that automates the data transformations, stores them and makes them available for training and inference. Features are input for machine learning models.

How to use SQL with Pandas?

MLWhiz

Pandas is one of the best data manipulation libraries in recent times. It lets you slice and dice, groupby, join and do any arbitrary data transformation.

Navigating the Data Provider Jungle

Dataiku

We speak a lot about the ways we can use data, transform it, and create powerful models based on advanced machine learning techniques, but we sometimes forget where the data comes from initially. Data Basics Featured