Sat.Nov 30, 2019 - Fri.Dec 06, 2019

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Data Governance 2.0: The CIO’s Guide to Collaborative Data Governance

erwin

In the data-driven era, CIO’s need a solid understanding of data governance 2.0 … Data governance (DG) is no longer about just compliance or relegated to the confines of IT. Today, data governance needs to be a ubiquitous part of your organization’s culture. As the CIO, your stakeholders include both IT and business users in collaborative relationships, which means data governance is not only your business, it’s everyone’s business.

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Make An Impact: Create More Value with Data Curation

TDAN

Wherever we go, we are overwhelmed by MORE: more sales, more discounts, more fun, more excitement, more features – the list goes on and on! What humans seem to be far less attuned to is reducing what we don’t need. Drive around any suburban neighborhood and see the many cars parked outside their garages! Believe […].

Sales 78
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6 Challenging Open Source Data Science Projects to Make you a Better Data Scientist

Analytics Vidhya

Overview Here are 6 challenging open-source data science projects to level up your data scientist skillset There are some intriguing data science projects, including. The post 6 Challenging Open Source Data Science Projects to Make you a Better Data Scientist appeared first on Analytics Vidhya.

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The Changing Role of the CDAO

Corinium

The proper powers and responsibilities for a CDAO to wield have been a topic of debate in the business world for some years now. However, it has become clear that having someone who is responsible for maximizing the value of a company’s data asset is essential for businesses operating in the digital age.

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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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10 Free Top Notch Machine Learning Courses

KDnuggets

Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.

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Predictive Tourism: The Merger Of Big Data In Travel Industry

Smart Data Collective

Data science has shifted the existing ether bringing in new marvelous opportunities to many industries. In line with these immense possibilities, comes rapid changes and challenges. And in this case, the travel and tourism industry is no exception here. Travel industry may not be the first to inculcate emerging technology for its benefit, but it sure is benefiting from it now.

Big Data 131

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. ln this post he describes where and how having “humans in the loop” in forecasting makes sense, and reflects on past failures and successes that have led him to this perspective. Our team does a lot of forecasting.

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Data Science Curriculum Roadmap

KDnuggets

What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.

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6 Data Analysis Methods to Help You Make Great Financial Statements

FineReport

The year is coming to an end, and if any of you work in the relevant departments of the company’s financial accounting, you must be busy preparing various annual financial statements. Especially for beginners who have just entered this field, how to design reports to clearly show the financial analysis and business operation status is a challenge. In the financial statements, compared to traditional dense tables, charts can visualize the data and display the data more intuitively, making the com

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Create Natural Language Processing-based Apps for iOS in Minutes! (using Apple’s Core ML 3)

Analytics Vidhya

Overview Intrigued by Apple’s iOS apps? Learn how to build Natural Language Processing (NLP) iOS apps in this article We’ll be using Apple’s Core. The post Create Natural Language Processing-based Apps for iOS in Minutes! (using Apple’s Core ML 3) appeared first on Analytics Vidhya.

Analytics 138
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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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Powerful SAP Reporting Doesn’t Require Heavy IT Department Involvement

Jet Global

Businesses that rely on SAP reporting to track their key performance indicators also typically rely on their IT department to facilitate initial report creation. Creating reports inside the SAP ecosystem involves the careful collection and integration of data in ways that only IT knows how to connect. It may seem absolutely necessary that tech professionals be required for a complex, data-driven process like reporting.

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Explainability: Cracking open the black box, Part 1

KDnuggets

What is Explainability in AI and how can we leverage different techniques to open the black box of AI and peek inside? This practical guide offers a review and critique of the various techniques of interpretability.

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Reporting Tool Beyond Excel: Dynamic and Automatic

FineReport

Why we need reporting tools? You can’t deny the fact that almost every position in the company is inseparable from reports. If you are a report producer, your job is to extract appropriate data and make reports according to key indicators; If you are a business staff, the basic components of your work are model + indicator + report +data visualization ; If you are an operation and maintenance staff, your job is to ensure that the company’s core reports are released on time.

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Data Science Immersive Bootcamp – Hands-on Internship with Job Guarantee!

Analytics Vidhya

“I have applied for various data science roles but I always get rejected because of a lack of experience.” This is easily the most. The post Data Science Immersive Bootcamp – Hands-on Internship with Job Guarantee! appeared first on Analytics Vidhya.

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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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Save Time and Reduce Errors in Your PeopleSoft Reporting

Jet Global

Financial reporting requires a significant amount of time, attention, and input to prepare reports that offer valuable analysis and deep insight into enterprise performance. Therefore, it’s easy to assume that reporting is always going to be difficult, consuming more time than companies would like and creating copious data errors along the way.

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The Essential Toolbox for Data Cleaning

KDnuggets

Increase your confidence to perform data cleaning with a broader perspective of what datasets typically look like, and follow this toolbox of code snipets to make your data cleaning process faster and more efficient.

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6 Tips for Data Teams to Improve Collaboration

Sisense

Blog. Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. In the right hands, data is the ultimate means to answer important business questions. The problem is that when data is used incorrectly, it still provides answers (just bad ones).

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How to write Web apps using simple Python for Data Scientists?

MLWhiz

A Machine Learning project is never really complete if we don’t have a good way to showcase it. While in the past, a well-made visualization or a small PPT used to be enough for showcasing a data science project, with the advent of dashboarding tools like RShiny and Dash, a good data scientist needs to have a fair bit of knowledge of web frameworks to get along.

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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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Qualifications to Become a Data Analyst

Data Science 101

Data Analysis as a career. Do you know which the sexiest job of the 21st Century is? As per the Harvard Business Review , it is Data Scientist. Though, technically, Data Scientists are a few notches above Data Analysts, becoming a Data Analyst makes it easier for you to become a Data Scientist. Picking a career is one of the most critical decisions that we need to take.

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A Non-Technical Reading List for Data Science

KDnuggets

The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.

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Unleash the Power of Advanced Analytics with the Sisense Q4 2019 Release

Sisense

Blog. “Data is the New Oil” was coined by The Economist in May 2017 and became a mantra for organizations to drive new wealth from data. But in reality, data by itself has no value. Even though we create a tremendous amount of it (90% of the world’s data was created in the past year), research shows that we are only using 1% of this data. The rapid growth of data volumes has effectively outstripped our ability to process and analyze it.

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The Data-Centric Revolution: Semantics and the DAMA Wheel

TDAN

Recently, I was giving a presentation and someone asked me which segment of “the DAMA wheel” did I think semantics most affected. I said I thought it affected all of them pretty profoundly, but perhaps the Metadata wedge the most. I thought I’d spend a bit of time to reflect on the question and answer […].

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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.

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Crafting Seamless Digital Experiences for a Connected Generation - The Connected Enterprise Holds The Keys To The King[CX]dom

Corinium

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Why software engineering processes and tools don’t work for machine learning

KDnuggets

While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists and teams can’t rely on software engineering tools and processes for machine learning.

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Finding the Right Reporting Narrative in Banking and Insurance

Jet Global

While financial reporting is largely standard across businesses no matter the industry—accounts receivable, inventory, etc.—when it comes to the banking and insurance industry, things get a little different. Because the banking industry makes money based on interest and fees, their revenue will look quite unlike, say, a technology company. Where the tech company will list their revenue line at the top, banking revenue is actually a total of net-interest income and non-interest income.

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4 Industries Shaken By The Artificial Intelligence Revolution

Smart Data Collective

Artificial intelligence has had a profound impact on our lives. A study by Tractica found that the global AI market is projected to grow to $118.6 billion within the next six years. The market for artificial intelligence technology is growing largely due to the number of industries that depend on it. Almost every industry can use AI technology in some capacity.

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

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

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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Demystifying Object Detection and Instance Segmentation for Data Scientists

MLWhiz

I like deep learning a lot but Object Detection is something that doesn’t come easily to me. And Object detection is important and does have its uses. Most common of them being self-driving cars, medical imaging and face detection. It is definitely a hard problem to solve. And with so many moving parts and new concepts introduced over the long history of this problem, it becomes even harder to understand.

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Enabling the Deep Learning Revolution

KDnuggets

Deep learning models are revolutionizing the business and technology world with jaw-dropping performances in one application area after another. Read this post on some of the numerous composite technologies which allow deep learning its complex nonlinearity.

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Questions to ask before building a Data Strategy

Data Science 101

Building a data strategy is a great idea. It helps to avoid many of the Challenges of a Data Science Projects. However, there are many questions to address before getting started. Below is a list of some of those questions. General Questions Before Starting a Data Strategy. Do you have a process for solving problems involving data? What are the biggest challenges in your business?

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What To Know About The Essence Of AI In Video Editing In 2020

Smart Data Collective

Artificial intelligence is playing a very important role in the future of video editing. Anybody that works in the profession should learn how to use AI technology to get the most value out of their videos. How can you use AI to benefit as a video editor ? Intelligent HQ founder Dinis Guarda has talked about some of the benefits of artificial intelligence for video editing in this article.

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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.