January, 2021

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9 Tips for a Seamless Transition to Data Science for Absolute Noobs!

Analytics Vidhya

ArticleVideos Overview The data science industry is growing exponentially It is important to have a clear understanding of the very basic questions before you. The post 9 Tips for a Seamless Transition to Data Science for Absolute Noobs! appeared first on Analytics Vidhya.

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How the Internet of Things and AI will Transform Sports Business?

Smart Data Collective

If there’s one industry that had previously remained fairly untouched from the technological advancements, it is the sports domain. However, over time the sector is getting introduced with several new generation technologies intended to make it efficient and smart. We have recently seen a number of technological developments that have impacted sports.

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Data-driven 2021: Predictions for a new year in data, analytics and AI

DataKitchen

The post Data-driven 2021: Predictions for a new year in data, analytics and AI first appeared on DataKitchen.

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Your Data Won’t Speak Unless You Ask It The Right Data Analysis Questions

datapine

In our cutthroat digital age, the importance of setting the right data analysis questions can define the overall success of a business. It is not just important to gather all the existing information, but to consider the preparation of data and utilize it in the proper way, has become an indispensable value in developing a successful business strategy.

IT 317
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Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

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Snowflake Builds on Its Success

David Menninger's Analyst Perspectives

Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data. Big data architectures have attempted to solve the problem with large pools of cost-effective storage, but in doing so have often created on-premises management and administration challenges.

IT 306
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PyCaret 2.2: Efficient Pipelines for Model Development

Domino Data Lab

Data science is an exciting field, but it can be intimidating to get started, especially for those new to coding. Even for experienced developers and data scientists, the process of developing a model could involve stringing together many steps from many packages, in ways that might not be as elegant or efficient as one might like. The creator of the Caret library in R (“short for C lassification A nd RE gression T raining”) was a software engineer named Max Kuhnwho sought to improve the situati

Modeling 145

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Customer Data Analytics is Critical to the Future of Account-Based Marketing

Smart Data Collective

We have talked at length about the importance of data analytics in the field of marketing. Data analytics offers many useful insights for companies striving to boost their market share. One of the best applications of data analytics is through enhanced account-based marketing. There are a lot of ways to use big data to get a better understanding of a target customer group, which is a vital part of any marketing strategy.

Marketing 144
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The Business Case for DataOps

DataKitchen

Savvy executives maximize the value of every budgeted dollar. Decisions to invest in new tools and methods must be backed up with a strong business case. As data professionals, we know the value and impact of DataOps: streamlining analytics workflows, reducing errors, and improving data operations transparency. Being able to quantify the value and impact helps leadership understand the return on past investments and supports alignment with future enterprise DataOps transformation initiatives.

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Data Intelligence in the Next Normal; Why, Who and When?

erwin

While many believe that the dawn of a new year represents a clean slate or a blank canvas, we simply don’t leave the past behind by merely flipping over a page in the calendar. As we enter 2021, we will also be building off the events of 2020 – both positive and negative – including the acceleration of digital transformation as the next normal begins to be defined.

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Introducing Precisely for Data Integrity

David Menninger's Analyst Perspectives

Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly. Without data integrity, organizations cannot trust the information produced by their data processes, and will be discouraged from using that data, resulting in inefficiencies and reduced effectiveness.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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The Art and Science of FP&A Storytelling

Timo Elliott

I recently participated in a web seminar on the Art and Science of FP&A Storytelling, hosted by the founder and CEO of FP&A Research Larysa Melnychuk along with other guests Pasquale della Puca , part of the global finance team at Beckman Coulter and Angelica Ancira , Global Digital Planning Lead at PepsiCo. With advanced analytics, flexible dashboarding and effective data visualization, FP&A storytelling has become both an art and science.

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An Quick Overview of Data Science Universe

Analytics Vidhya

ArticleVideos This article was published as a part of the Data Science Blogathon. What is Data Science (DS)? Data Science is a blend of. The post An Quick Overview of Data Science Universe appeared first on Analytics Vidhya.

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Big Data Plays Key Role in Helping Satellites Get Launched into Orbit

Smart Data Collective

Big data is changing the space race in ways that original founders at NASA and other global space exploration organizations never foresaw decades ago. Miriam Kramer, an author with Axios, talked about the growing number of space companies that are finding new ways to utilize big data. They hope new advances in data technology will help them connect with new markets.

Big Data 144
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Do You Need a DataOps Dojo?

DataKitchen

As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. Centralizing analytics brings it under control but granting analysts free reign is necessary to foster innovation and stay competitive. The beauty of DataOps is that you don’t have to choose between centralization and freedom.

Metrics 243
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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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Building a Machine Learning Application With Cloudera Data Science Workbench And Operational Database, Part 1: The Set-Up & Basics

Cloudera

Introduction. Python is used extensively among Data Engineers and Data Scientists to solve all sorts of problems from ETL/ELT pipelines to building machine learning models. Apache HBase is an effective data storage system for many workflows but accessing this data specifically through Python can be a struggle. For data professionals that want to make use of data stored in HBase the recent upstream project “hbase-connectors” can be used with PySpark for basic operations.

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Tableau and Salesforce bring New Look to Business Analytics

David Menninger's Analyst Perspectives

Businesses are transforming their organizations, building a data culture and deploying sophisticated analytics more broadly than ever. However, the process of using data and analytics is not always easy. The necessary tools are often separate, but our research shows organizations prefer an integrated environment. In our Data Preparation Benchmark Research , we found that 41% of participants use Analytics and Business Intelligence tools for data preparation.

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Improving Population Health Through Citizen 360

Teradata

By leveraging data to create a 360 degree view of its citizenry, government agencies can create more optimal experiences & improve outcomes such as closing the tax gap or improving quality of care.

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5 Python Packages Every Data Scientist Must Know

Analytics Vidhya

ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction When it comes to productivity, the internet is flooded with. The post 5 Python Packages Every Data Scientist Must Know appeared first on Analytics Vidhya.

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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How Machine Learning Enhances Momentum of Cryptocurrency Price Movements

Smart Data Collective

Cryptocurrencies have become very important in the modern economy. They have also created numerous opportunities for informed investors to create diversified portfolios and take advantage of a market for assets that provide an exceptional ROI. Machine learning technology has made cryptocurrency investing opportunities more lucrative than ever. The impact of machine learning on the market for bitcoin and other cryptocurrencies is multifaceted.

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DataOps Reports that Keep Your Finger on the Pulse

DataKitchen

It’s never good when your boss calls at 5 pm on a Friday. “The weekly analytics didn’t build correctly. What happened? Call me every hour with updates until you figure it out!”. For many data professionals, this situation is all too familiar. Analytics, in the modern enterprise, span toolchains, teams, and data centers. Large enterprises ingest data from dozens or hundreds of internal and external data sources.

Reporting 243
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30 Best Manufacturing KPIs and Metric Examples for 2021 Reporting

Jet Global

What is an Operations KPI? An Operations Key Performance Indicator (KPI) or metric is a discrete measurement that a company uses to monitor and evaluate the efficiency of its day-to-day operations. These operations KPIs help management identify which operational strategies are effective, and those that inhibit the company. Why Your Company Should Be Using Operational Metrics to Stay Competitive.

Metrics 131
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Cloudera Consolidates Its Data Platform

David Menninger's Analyst Perspectives

Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs. A combination of complex data lake and data warehouse capabilities are required to leverage this data. Our research shows that nearly three-quarters of organizations deploy both data lakes and data warehouses but are using a variety of approaches which can be cumbersome.

Data Lake 269
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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A First Look at Gen 2 Composite Models with Live Power BI Datasets

Paul Turley

About three years ago when the data model development engineers from the Power BI product team told me they were working on the ability for tabular data models to share other published data models, that sounded amazing and almost too good to be true.

Modeling 131
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Understanding Architecture of LSTM

Analytics Vidhya

ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction “Machine intelligence is the last invention that humanity will ever. The post Understanding Architecture of LSTM appeared first on Analytics Vidhya.

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Blockchain: The Fall of Traditional Centralized Systems in Business & Finance

Smart Data Collective

Blockchain is one of the most important technologies to shape the world. One of the biggest industries that has been affected has been finance. The market for blockchain technology in the financial sector is expected to reach over $3 billion by 2024. The question many experts are asking is: “what factors are driving the growth in blockchain in the financial industry?

Finance 139
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DataOps Facilitates Remote Work

DataKitchen

Remote working has revealed the inconsistency and fragility of workflow processes in many data organizations. The data teams share a common objective; to create analytics for the (internal or external) customer. Execution of this mission requires the contribution of several groups: data center/IT, data engineering, data science, data visualization, and data governance.

Testing 147
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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.

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Chart Selection Guide

The Data Visualisation Catalogue

On the site’s Instagram , there’s a series of posts that each list with icons, the chart types recommended based on what you can communicate or analyse with them. In total, there were 15 posts created, each with a particular category and color theme. Essentially, these were an updated, Instagram version of the ‘What do you want to show’ page here on the site, but with some new types of charts covered.

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Emerging Data Platforms Tackle Big Challenges

David Menninger's Analyst Perspectives

Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets. Organizations still struggle with limited data visibility and insufficient insights, which are often caused by a multitude of reasons such as analytic workloads runn

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Object Detection With Deep Learning on Aerial Imagery

Dataiku

Imagine you’re in a landlocked country, and a mystery infection has spread. The government has fallen, and rebels are roaming the country. If you’re the armed forces in this scenario, how do you make decisions in this environment? How can you fully understand the situation at hand?

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A Quick Introduction to K – Nearest Neighbor (KNN) Classification Using Python

Analytics Vidhya

ArticleVideos This article was published as a part of the Data Science Blogathon. Introduction This article concerns one of the supervised ML classification algorithm-KNN(K. The post A Quick Introduction to K – Nearest Neighbor (KNN) Classification Using Python appeared first on Analytics Vidhya.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.