CIO Business Intelligence

SEPTEMBER 14, 2022

technologies that fueled data strategies aimed at identifying inefficiencies, streamlining processes, and improving the ability to forecast and predict industry trends. The average salary for a financial software engineer is $119,593 per year, with a reported salary range of $88,000 to $177,000 per year, according to data from Glassdoor.

Manufacturing 111

Manufacturing IT Software Digital Transformation 111

DataKitchen

OCTOBER 25, 2022

Part 2: Introducing Data Journeys. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.

Testing 130

Testing Data-driven Visualization Dashboards 130

CIO Business Intelligence

JUNE 28, 2022

Some call data the new oil. Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

Management 132

Management Internet of Things Statistics Data-driven 132

DataKitchen

MARCH 16, 2023

How to measure your data analytics team? So it’s Monday, and you lead a data analytics team of perhaps 30 people. Like most leaders of data analytic teams, you have been doing very little to quantify your team’s success. What should be in that report about your data team? What should I track? Introduction.

Metrics 130

Metrics Data Analytics Analytics Measurement 130

DataKitchen

JANUARY 5, 2021

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. Data Science Workflow – Kubeflow, Python, R. Data Engineering Workflow – Airflow, ETL.

Testing 147

Testing Data Governance Metadata Visualization 147

Smart Data Collective

APRIL 25, 2022

Data science is a broad field that can help organizations glean significant insights into various aspects of their operations. Whether it’s uncovering truths about customer buying habits or discovering new ways to make teams collaborate more efficiently, data science can be an extremely useful tool to all who take advantage of it.

Data Science 124

Data Science Cost-Benefit Sales Technology 124

CIO Business Intelligence

MAY 27, 2022

Liberty Mutual’s data scientists employ Tableau and Python extensively to deploy models into production. And that is in no small part thanks to the vision of James McGlennon, who in his role as CIO of Liberty Mutual for past 17 years has led the charge to the cloud, analytics, and AI with a budget north of $2 billion.

Insurance 89

Insurance Machine Learning Digital Transformation Cost-Benefit 89

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Visual IDE for data pipelines; RPA for rote tasks. Highlights.

Predictive Analytics 136

Predictive Analytics Analytics Statistics Machine Learning 136

DataKitchen

NOVEMBER 18, 2022

Part 3: Considering the Elements of Data Journeys. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately. (Part 1) (Part 2). Alerting paths.

Testing 130

Testing Statistics Measurement Metrics 130

O'Reilly on Data

NOVEMBER 18, 2019

In this interview from O’Reilly Foo Camp 2019, Hands-On Unsupervised Learning Using Python author Ankur Patel discusses the challenges and opportunities in making machine learning and AI accessible and financially viable for enterprise applications. ” ( 00:57 ). ” ( 01:57 ).

ROI 132

ROI Unstructured Data Machine Learning Modeling 132

datapine

MARCH 31, 2022

Does data excite, inspire, or even amaze you? Despite these findings, the undeniable value of intelligence for business, and the incredible demand for BI skills, there is a severe shortage of BI-based data professionals – with a shortfall of 1.5 2) Top 10 Necessary BI Skills. 3) What Are the First Steps To Getting Started?

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataKitchen

MAY 10, 2021

Data errors impact decision-making. Data errors infringe on work-life balance. Data errors also affect careers. If you have been in the data profession for any length of time, you probably know what it means to face a mob of stakeholders who are angry about inaccurate or late analytics.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Domino Data Lab

FEBRUARY 19, 2021

spaCy is a python library that provides capabilities to conduct advanced natural language processing analysis and build models that can underpin document analysis, chatbot capabilities, and all other forms of text analysis. ", "David joined Domino Data Lab in February 2020." Bench-marking data from [link].

Enterprise 119

Enterprise Data Science Modeling Visualization 119

Sisense

MAY 27, 2019

That means there’s one Hell of a lot of data running through your organization. So, given the choice, which analytics job title should you choose: A data engineer or a data scientist? Digging Deep For Data Diamonds – The Data Engineer. Data’s like diamonds. That’s the job of the data engineer.

Statistics 75

Statistics Machine Learning Visualization Big Data 75

CIO Business Intelligence

MARCH 16, 2022

The pace of technology has evolved so rapidly over the last few years, multiplied by the pandemic, that it’s hard to keep track — and what’s most in demand today may be obsolete tomorrow. Kiran Marri, chief scientist at CSS Corp., Identifying which emerging technologies will prove most useful is a challenge, though.

Forecasting 92

Forecasting Machine Learning Technology Enterprise 92

Smart Data Collective

JUNE 10, 2019

If you are a data developer, then you need to invest in learning the right programming languages. Python is one of the most important languages for data science. The popularity of python has been on the rise and is showing no signs of waning. Not many data scientists specialize in JavaScript programming.

IoT 84

IoT Machine Learning Interactive Data Science 84

AWS Big Data

SEPTEMBER 20, 2023

IAM VPC rules – You can require your users to use (or restrict them from using) certain VPCs or subnets for the sessions, to comply with your corporate policies and have control over how your data travels in the network. Optionally, if you want to use run a local notebook from your computer, install Python 3.7

Interactive 94

Interactive Management Reporting IT 94

IBM Big Data Hub

AUGUST 11, 2023

The advancement of computing power over recent decades has led to an explosion of digital data, from traffic cameras monitoring commuter habits to smart refrigerators revealing how and when the average family eats. Both computer scientists and business leaders have taken note of the potential of the data.

Data Science 56

Data Science Machine Learning Cost-Benefit Deep Learning 56

FineReport

DECEMBER 9, 2021

A business intelligence strategy is a framework that enables enterprises to use the right BI tools to analyze the correct data and then report to the right people to aid in making the right decisions. These goals include optimizing current business processes, creating top-notch products and services, and becoming a data-driven business.

Strategy 98

Strategy Business Intelligence KPI Key Performance Indicator 98

Domino Data Lab

MAY 1, 2019

This Domino Data Science Field Note provides highlights and excerpted slides from Chloe Mawer ’s “ The Ingredients of a Reproducible Machine Learning Model ” talk at a recent WiMLDS meetup. Mawer is a Principal Data Scientist at Lineage Logistics as well as an Adjunct Lecturer at Northwestern University.

Machine Learning 81

Machine Learning Testing Data Science Modeling 81

DataRobot Blog

MARCH 10, 2022

By utilizing artificial intelligence, organizations can dissolve production bottlenecks, track and minimize/maximize critical KPIs like scrap rate and production rates, and get ahead of the power curve to accelerate their distribution and delivery channels. Time-Series Forecasting?—? Leveraging Snowflake and DataRobot for Speed and Scale.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

Cloudera

JANUARY 30, 2019

It’s official – Cloudera and Hortonworks have merged , and today I’m excited to announce the availability of Cloudera Data Science Workbench (CDSW) for Hortonworks Data Platform (HDP). Trusted by large data science teams across hundreds of enterprises —. Sound familiar? What is CDSW? Install any library or framework (e.g.

Data Science 72

Data Science Machine Learning Experimentation Cost-Benefit 72

DataRobot

JUNE 23, 2021

As they strive to improve models, data scientists continually try new approaches to refine their predictions. To help data scientists experiment faster, DataRobot has added Composable ML to automated machine learning. In data science , the best results come through experimentation. So let’s dig in! Run AutoPilot.

Machine Learning 52

Machine Learning Modeling Experimentation Visualization 52

The Unofficial Google Data Science Blog

NOVEMBER 19, 2015

We will continue to bring you posts from the range of data science activities at Google. We briefly highlight some of the things we look for in data scientists we hire at Google and give tips on ways to prepare. At Google we’re always looking for talented people, and we’re interested in hiring great data scientists.

Statistics 75

Statistics Data Science Machine Learning Sales 75

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure? Organizations need to recast storing their data.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

AWS Big Data

MARCH 18, 2024

It always pays to know more about your customers, and AWS Data Exchange makes it straightforward to use publicly available census data to enrich your customer dataset. The United States Census Bureau conducts the US census every 10 years and gathers household survey data. Subscribe to census data on AWS Data Exchange.

Data Warehouse 79

Data Warehouse Visualization Snapshot Data-driven 79

Sisense

JANUARY 15, 2021

In Building Bridges , we focus on helping end users, app builders, and data experts select and roll out analytics platforms easily and efficiently. We live in a world driven by data. As we have previously posted, the BI group is often the department that approaches the data teams for access to an analytics solution.

Analytics 75

Analytics Data-driven Business Intelligence Visualization 75

Cloudera

MAY 22, 2018

Cloudera Data Science Workbench (CDSW) makes secure, collaborative data science at scale a reality for the enterprise and accelerates the delivery of new data products. As data scientists iteratively develop models, they often experiment with datasets, features, libraries, and algorithms as well as tuning hyperparameters.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. Types of Modeling Tools.

Modeling 64

Modeling IT Risk Management Deep Learning 64

bridgei2i

JANUARY 25, 2022

The Basic Guide to Data Science at the Workplace. The Basic Guide to Data Science at the Workplace. In this podcast episode, AI enthusiasts Anirudh and Janci talk about how sincere curiosity and passion for learning can help anyone understand data science and become an active contributor. And now you’re a data scientist.

Data Science 52

Data Science Machine Learning Data-driven Statistics 52

DataRobot

SEPTEMBER 17, 2021

Other companies implement decision rules, but do it by writing their own Python, Java or SQL. Our decision flow editor is an intuitive GUI that lets you easily create rules by point and click, then see how data flows through a decision flowchart that embeds both your business knowledge and your AI models. Want to Learn More?

Forecasting 52

Forecasting Predictive Modeling Machine Learning Cost-Benefit 52

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 101

Data Lake Management Metrics Data Warehouse 101

IBM Big Data Hub

SEPTEMBER 7, 2022

There are still not enough data experts out there, even as the world of data evolves rapidly. We started the Summer School for Data Leaders five years ago to create a community for data experts to share ideas and relate to people facing similar challenges. Data ethics is top of mind. The community is growing.

Data Strategy 52

Data Strategy Strategy Data-driven Data Quality 52

Data Science 101

MAY 6, 2019

At Springboard , we recently sat down with Michael Beaumier, a data scientist at Google, to discuss his transition into the field, what the interview process is like, the future of data wrangling, and the advice he has for aspiring data professionals. in physics and now you’re a data scientist.

Data Science 98

Data Science Modeling Machine Learning Testing 98

Sisense

JUNE 6, 2019

But frankly, as a data geek, it is a pretty boring report. As a data geek, I want to know exactly why we performed so well! Published a few months after the MQ, this report provides more than a glimpse at the mountain of data behind the Gartner MQ. At Sisense, we make sure data teams have the best tools to ingest, clean, and.

Reporting 75

Reporting Business Intelligence Visualization Digital Transformation 75