Analytics Vidhya
SEPTEMBER 29, 2020
Overview Winning data science competitions can be a complex process – but you can crack the top 3 if you have a framework to. The post How I Became a Data Science Competition Master from Scratch appeared first on Analytics Vidhya.
Analytics Vidhya
SEPTEMBER 27, 2020
Overview Microsoft Excel is an excellent tool for learning and executing statistical functions Here are 12 statistical functions in Excel that you should master. The post 10 Statistical Functions in Excel every Analytics Professional Should Know appeared first on Analytics Vidhya.
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O'Reilly on Data
SEPTEMBER 8, 2020
In a conversation with Kevlin Henney, we started talking about the kinds of user interfaces that might work for AI-assisted programming. This is a significant problem: neither of us were aware of any significant work on user interfaces that support collaboration. Most AI systems we’ve seen envision AI as an oracle: you give it the input, it pops out the answer.
datapine
SEPTEMBER 1, 2020
To answer the question, “how can I get the answers I need to solve the new business challenges I face every day?”, there are two answers that go hand in hand: good exploitation of your analytics, that come from the results of a market research report. Market research analyses are the go-to solution for many professionals, and with reason: they save time, they provide new insights and clarification on the business market you are working on and help you to refine and polish your strategy.
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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?
Corinium
SEPTEMBER 21, 2020
COVID-19 has affected workplaces everywhere, the impacts of which could greatly alter how different organizations will approach the way they do business. The need to identify and prepare for a shift in operations and strategic goals is incredibly important. Organisations that respond efficiently can have a major role in establishing their companies as top competitors within their respective industries.
BA Learnings
SEPTEMBER 26, 2020
According to a study conducted by IBM in 2012, companies that perform well tend to innovate their business models quite frequently, compared to underperformers. Innovation is essential to remaining competitive if a business is to stay afloat and remain relevant. History provides examples of companies that have lost out by missing out on opportunities to innovate – Think Motorola, Nokia, Lehman Brothers, Kodak, American Airlines – the list goes on.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
SEPTEMBER 28, 2020
Overview Amazon Web Services (AWS) is the leading cloud platform for deploying machine learning solutions Every data science professional should learn how AWS works. The post What is AWS? Why Every Data Science Professional Should Learn Amazon Web Services appeared first on Analytics Vidhya.
O'Reilly on Data
SEPTEMBER 15, 2020
AI Benefits and Stakeholders. AI is a field where value, in the form of outcomes and their resulting benefits, is created by machines exhibiting the ability to learn and “understand,” and to use the knowledge learned to carry out tasks or achieve goals. AI-generated benefits can be realized by defining and achieving appropriate goals. These goals depend on who the stakeholder is; in other words, the person or company receiving the benefits.
Smart Data Collective
SEPTEMBER 21, 2020
Two or three decades ago, gathering data was the biggest challenge businesses faced. Leaders craved more information and access. Today, these same companies are drowning in data. The challenge of today is organizing and making sense of the data. 4 Tips to Help You Make Sense of Your Data. With so much emphasis on collecting and accessing data, it’s easy to become so paralyzed by information that you fail to do anything with it.
erwin
SEPTEMBER 3, 2020
Aligning these practices for regulatory compliance and other benefits. Why should you integrate data governance (DG) and enterprise architecture (EA)? It’s time to think about EA beyond IT. Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change.
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📌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.
BA Learnings
SEPTEMBER 26, 2020
According to a study conducted by IBM in 2012, companies that perform well tend to innovate their business models quite frequently, compared to underperformers. Innovation is essential to remaining competitive if a business is to stay afloat and remain relevant. History provides examples of companies that have lost out by missing out on opportunities to innovate – Think Motorola, Nokia, Lehman Brothers, Kodak, American Airlines – the list goes on.
Boris Evelson
SEPTEMBER 21, 2020
The perception of legacy enterprise business intelligence (BI) platforms comes with some legitimate stigma and baggage. It’s technology first, not business-led; the graphical user interface (GUI)-based user experience (UX) doesn’t address ease of use for all business decision-makers; there are too many underutilized reports and dashboards floating around in the enterprise; and signals produced by […].
Analytics Vidhya
SEPTEMBER 21, 2020
Overview NoSQL databases are ubiquitous in the industry – a data scientist is expected to be familiar with these databases Here, we will see. The post 5 Popular NoSQL Databases Every Data Science Professional Should Know About appeared first on Analytics Vidhya.
MLWhiz
SEPTEMBER 7, 2020
PyTorch has sort of became one of the de facto standards for creating Neural Networks now, and I love its interface. Yet, it is somehow a little difficult for beginners to get a hold of. I remember picking PyTorch up only after some extensive experimentation a couple of years back. To tell you the truth, it took me a lot of time to pick it up but am I glad that I moved from Keras to PyTorch.
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.
Smart Data Collective
SEPTEMBER 17, 2020
Nowadays, terms like ‘Data Analytics,’ ‘Data Visualization,’ and ‘Big Data’ have become quite popular. These terms are fundamentally tied predominantly to matters involving digital transformation as well as growth in companies. In this modern age, each business entity is driven by data. Data analytics are now very crucial whenever there is a decision-making process involved.
erwin
SEPTEMBER 17, 2020
Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. Critically, it makes it easier to get a clear view of how information is created and flows into, across and outside an enterprise. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.
Cloudera
SEPTEMBER 28, 2020
Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Cloudera has found that customers have spent many years investing in their big data assets and want to continue to build on that investment by moving towards a more modern architecture that helps leverage the multiple form factors.
FineReport
SEPTEMBER 2, 2020
Free data visualization tools are professional in different categories: dashboard, chart, maps, network, and so on. Today, let’s review the top free data visualization tools on the market. What are the Benefits of Using Free Data Visualization Tools? The most significant advantage is free, and open-source data visualization tools can help you control your budget.
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.
Analytics Vidhya
SEPTEMBER 17, 2020
Introduction A virtual assistant, also called an AI assistant or digital assistant, is an application program that understands natural language voice commands and completes. The post How to create your AI Virtual Assistant using Python appeared first on Analytics Vidhya.
TDAN
SEPTEMBER 1, 2020
Getting the business engaged with data governance can sometimes be a challenge. Any sort of driver to make that a more organic experience for your organization will be an asset. At NAIT (the Northern Alberta Institute of Technology), we have put together a process to visually identify and connect our reports to Data Governance. The […].
Smart Data Collective
SEPTEMBER 23, 2020
The concept of cryptocurrency is still foreign to so many in the United States and around the world. There is a lot more mass appeal of cryptocurrencies like Bitcoin, Litecoin, and others. Generally speaking, though, they are still mysterious in the eyes of the common individual. In the cryptocurrency market, we are starting to see the emergency and convergence of crypto and big data analytics.
erwin
SEPTEMBER 10, 2020
Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. In a previous blog , I explained that data lineage is basically the history of data, including a data set’s origin, characteristics, quality and movement over time.
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.
Cloudera
SEPTEMBER 29, 2020
Performance is one of the key, if not the most important deciding criterion, in choosing a Cloud Data Warehouse service. In today’s fast changing world, enterprises have to make data driven decisions quickly and for that they rely heavily on their data warehouse service. . In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to Microsoft HDInsight (also powered by Apache Hive-LLAP) on Azure using the TPC-DS 2.9 benchmark.
Dataiku
SEPTEMBER 4, 2020
In the previous three posts in the How They Work (In Plain English!) series, we went through a high-level overview of machine learning and took a deep dive into two key categories of supervised learning algorithms — linear and tree-based models — and the most popular unsupervised learning technique, clustering. Today, we’ll dive into a second key unsupervised learning technique — dimensionality reduction.
Analytics Vidhya
SEPTEMBER 9, 2020
In this article, we bust 11 common myths people have about data science. We have divided the myths into career, tools and role related categories. The post Busted! 11 Data Science Myths You Should Avoid at All Costs appeared first on Analytics Vidhya.
TDAN
SEPTEMBER 1, 2020
We just finished a conversation with a client who was justifiably proud of having centralized what had previously been a very decentralized business function (in this case, it was HR, but it could have been any of a number of functions). They had seemingly achieved many of the benefits of becoming data-centric through decentralization: all […].
Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage
Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.
Smart Data Collective
SEPTEMBER 2, 2020
The market for cloud computing is growing at an insane pace. One analysis shows that it is likely to reach $761 billion by 2027. You might be surprised to know how much of a role it will play in the future of modern business. If it hadn’t been for massive advances in modern technology, the world would have been a completely different platform for modern businesses.
erwin
SEPTEMBER 25, 2020
Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. It serves as a visual guide in designing and deploying databases with high-quality data sources as part of application development. Data modeling has been used for decades to help organizations define and categorize their data, establishing standards and rules so it can be consumed and then u
Cloudera
SEPTEMBER 14, 2020
Everybody needs more data and more analytics, with so many different and sometimes often conflicting needs. Data engineers need batch resources, while data scientists need to quickly onboard ephemeral users. Data architects deal with constantly evolving workloads and business analysts must balance the urgency and importance of a concurrent user population that continues to grow.
Dataiku
SEPTEMBER 17, 2020
Moving from one phase of AI maturity to the next is significantly easier said than done. In fact, a recent benchmarking study of senior executives in over 1,200 companies revealed how few organizations are truly advanced in their maturity — 20% are “beginners” in AI, 32% are “early implementers” starting to pilot AI and use simple applications, 33% are “advancers” using AI in key parts of their business and seeing gains, and only 15% are “leaders” widely using AI to drive tangible benefits.
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The complexity of financial data, the need for real-time insight, and the demand for user-friendly visualizations can seem daunting when it comes to analytics - but there is an easier way. With Logi Symphony, we aim to turn these challenges into opportunities. Our platform empowers you to seamlessly integrate advanced data analytics, generative AI, data visualization, and pixel-perfect reporting into your applications, transforming raw data into actionable insights.
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