Analytics Vidhya
JANUARY 4, 2021
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.
Smart Data Collective
JANUARY 6, 2021
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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datapine
JANUARY 24, 2021
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.
DataKitchen
JANUARY 4, 2021
The post Data-driven 2021: Predictions for a new year in data, analytics and AI first appeared on DataKitchen.
Speaker: Timothy Chan, PhD., Head of Data Science
Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
David Menninger's Analyst Perspectives
JANUARY 15, 2021
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.
erwin
JANUARY 14, 2021
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.
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Smart Data Collective
JANUARY 22, 2021
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.
Timo Elliott
JANUARY 4, 2021
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.
DataKitchen
JANUARY 6, 2021
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.
David Menninger's Analyst Perspectives
JANUARY 25, 2021
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.
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.
Cloudera
JANUARY 6, 2021
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.
Analytics Vidhya
JANUARY 26, 2021
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.
Smart Data Collective
JANUARY 20, 2021
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.
Teradata
JANUARY 5, 2021
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.
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.
DataKitchen
JANUARY 20, 2021
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.
David Menninger's Analyst Perspectives
JANUARY 20, 2021
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.
Jet Global
JANUARY 8, 2021
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.
Analytics Vidhya
JANUARY 26, 2021
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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Smart Data Collective
JANUARY 19, 2021
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?
Paul Turley
JANUARY 11, 2021
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.
DataKitchen
JANUARY 25, 2021
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.
David Menninger's Analyst Perspectives
JANUARY 14, 2021
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
Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO
The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.
Dataiku
JANUARY 5, 2021
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?
Analytics Vidhya
JANUARY 21, 2021
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.
Smart Data Collective
JANUARY 27, 2021
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.
Sisense
JANUARY 6, 2021
Blog. What are white-labeled reports White-label reports: Under the hood Exploring white-label dashboards Use case snapshots Horsepower under the hood. Every company is becoming a data company. Data-Powered Apps delves into how product teams are infusing insights into applications and services to build products that will delight users and stand the test of time.
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Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.
Occam's Razor
JANUARY 4, 2021
Like you, I consume a whole lot of reports every day – company data, public data. Many are acceptable, some are very good and all the rest leave me extremely frustrated with both the ink and the think. People make so many obvious mistakes. Sometimes repeatedly. Just yesterday I was quietly seething because none of visuals included in the report contained any context to understand if the performance I was looking at was good or bad.
Cloudera
JANUARY 20, 2021
In this last installment, we’ll discuss a demo application that uses PySpark.ML to make a classification model based off of training data stored in both Cloudera’s Operational Database (powered by Apache HBase) and Apache HDFS. Afterwards, this model is then scored and served through a simple Web Application. For more context, this demo is based on concepts discussed in this blog post How to deploy ML models to production.
Dataiku
JANUARY 29, 2021
While the earliest known use of the term “business intelligence” (BI) dates back to 1865 , it wasn’t until nearly a century later that computer scientist Hans Peter Luhn — known today as the “Father of Business Intelligence” — released a paper “A Business Intelligence System” that began to really identify and break down technology’s role as an enabler of BI.
Analytics Vidhya
JANUARY 20, 2021
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.
Advertiser: Data Robot
As technology transforms the global business landscape, companies need to examine and update their internal processes for innovation to keep pace. Ultimately, organizations will have to improve the velocity of innovation by creating repeatable processes that support ideation, exploration, and incubation, essential to capturing an idea’s full value.
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