datapine

DECEMBER 4, 2019

Each year, we hear about buzzwords that enter the community, language, market and drive businesses and companies forward. That’s why we have prepared a list of the most prominent business intelligence buzzwords that will dominate in 2020. The accuracy of the predictions depends on the data used to create the model.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212

CIO Business Intelligence

APRIL 10, 2024

Higher-level languages, automation, low-code and no-code development platforms, and better programming environments have been gradually reducing the need for IT staff to perform low-level, routine tasks for years so they can take on more innovative challenges. It’s not like personality, which is pretty hard wired,” he says.

Consulting 131

Consulting Technology Management Software 131

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

datapine

SEPTEMBER 16, 2022

Previously, we discussed the top 19 big data books you need to read, followed by our rundown of the world’s top business intelligence books as well as our list of the best SQL books for beginners and intermediates. Data visualization, or ‘data viz’ as it’s commonly known, is the graphic presentation of data.

Visualization 304

Visualization Dashboards Data-driven Statistics 304

Smart Data Collective

AUGUST 10, 2021

In today’s market, it’s hard to thrive or even just survive without collecting data. Data can help them create strategies based on these powerful forces. The good news is that it’s never been easier to collect and organize data. The good news is that it’s never been easier to collect and organize data.

Analytics 127

Analytics Data-driven Advertising Data Science 127

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

Data Science 101

NOVEMBER 8, 2023

Drawing straws in my head, I’m going to have to go with my recent promotion from an analytics/development role (big data marketing segmentation would maybe be the best way to describe it) to a product management role… But it wasn’t the promotion that was significant. I have felt a lot more confident since that moment.

Data Science 59

Data Science Visualization Management Data Processing 59

Domino Data Lab

JUNE 15, 2021

These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. The typical data science journey for a company starts with a small team that is tasked with a handful of specific problems.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Cloudera

DECEMBER 15, 2022

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), Cloudera customers, such as Teranet , have built open lakehouses to future-proof their data platforms for all their analytical workloads. Cloudera partners are also benefiting from Apache Iceberg in CDP. Advanced capabilitie.

Metadata 78

Metadata Data Warehouse Snapshot Data Quality 78

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. ” Romain Gaborit, CTO, Eviden, an ATOS business “We’re looking at the potential usage of Large Language Models. What is watsonx.data?

Machine Learning 63

Machine Learning Data Warehouse Modeling Cost-Benefit 63

DataRobot

DECEMBER 16, 2021

DataRobot Core for Expert Data Scientists: Build Fast and Deliver at Scale with a Code-First Experience. Launched today, DataRobot Core is a comprehensive offering aimed at giving data scientists the purpose-built technologies they need to deliver powerful AI solutions for their organizations quickly, with a code-first experience.

Forecasting 98

Forecasting Modeling Data-driven Data Science 98

Smart Data Collective

OCTOBER 14, 2019

From the tech industry to retail and finance, big data is encompassing the world as we know it. More organizations rely on big data to help with decision making and to analyze and explore future trends. Big Data Skillsets. billion allocated for data center systems and $90.2 NoSQL and SQL. billion for IT services.

Big Data 74

Big Data Software Data mining Prescriptive Analytics 74

IBM Big Data Hub

MARCH 25, 2022

A database is a crucial engine for a world becoming more data driven. Businesses are more heavily relying on smart insights and emerging patterns to succeed. Advancements in software and hardware had an interplay between the rising appetite for any organization making a data-driven decision.

Data-driven 70

Data-driven Data Warehouse Data Processing Marketing 70

Smarten

SEPTEMBER 15, 2019

How About Giving Your Business Users the Power to Prepare Data for Analysis? Can Your Business Achieve Self-Serve Data Prep? Data prep does not have to be something your IT or data science staff does. If you want to find out more about Self-Serve Data ETL , start here: Augmented Data Preparation.

Machine Learning 54

Machine Learning Data Science Reporting Analytics 54

Sisense

OCTOBER 14, 2020

Here, we focus on the role of the data team in successfully applying advanced analytics and ensuring that you get the most from your data to make your organization truly data-driven. Smart organizations already appreciate the power of data and its influence on building successful strategies. Why build your data team?

Data-driven 98

Data-driven Machine Learning Dashboards Sales 98

Sisense

FEBRUARY 24, 2021

Whatever a company does, how it uses data is a key differentiator in its success or failure. Whether that data is generated internally or gathered from an external application used by customers, organizations now use on-demand cloud computing resources to make sense of the data, discover trends, and make intelligent forecasts.

Data Warehouse 69

Data Warehouse Big Data Metrics Visualization 69

Smart Data Collective

MAY 20, 2019

We’re well past the point of realization that big data and advanced analytics solutions are valuable — just about everyone knows this by now. Big data alone has become a modern staple of nearly every industry from retail to manufacturing, and for good reason. That’s equal to 44 zettabytes of data, or 44 trillion gigabytes.

Analytics 111

Analytics Machine Learning Business Intelligence Big Data 111

The Unofficial Google Data Science Blog

SEPTEMBER 9, 2015

by SEAN GERRISH and AMIR NAJMI To deliver the services our users have come to rely upon, Googlers have to process a lot of data — often at web-scale. In this post, we’ll describe some things we have learned about mixing declarative and procedural programing paradigms to simplify MapReduce as used by data scientists.

Data Science 56

Data Science Statistics Testing Metadata 56

Sisense

SEPTEMBER 9, 2019

Mark’s team is constantly adapting to and meeting the challenges of a rapidly evolving business using cloud technologies, real-time analytics, data warehousing, and virtualization. What if we could use this data to focus our resources and deliver better products? Predicting Return Rates On New Products.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

Sisense

FEBRUARY 24, 2020

What is the ultimate goal of using data internally at your organization? You probably answered something like “Make smarter, data-driven decisions.” You probably answered something like “Make smarter, data-driven decisions.” Developing analytic apps is a bold new direction for product teams.

Analytics 72

Analytics Metrics Data-driven Interactive 72

AWS Big Data

SEPTEMBER 29, 2023

In today’s digital age, data is at the heart of every organization’s success. One of the most commonly used formats for exchanging data is XML. Analyzing XML files can help organizations gain insights into their data, allowing them to make better decisions and improve their operations.

Metadata 65

Metadata Visualization Data-driven Optimization 65

Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins advised that data scientists ingest business problems, re-frame them as ML tasks, execute on the ML tasks, and then clearly and concisely communicate the results back to the organization.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Insight

MAY 8, 2019

In an ideal world, data scientists would focus their time on analysis and modeling, but there is often seemingly unavoidable overhead in visualizing and presenting their results. I was inspired to offer an alternative to both of these options at Insight, when I saw how long data science Fellows were taking to deploy their Flask apps.

Data Processing 72

Data Processing Testing Data Science Visualization 72

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. Data pipeline orchestration.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy. Discover why.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

JUNE 12, 2019

At Sisense, our mission is to empower users of all kinds with deep insights from even the most complex data. Soon after, we announced the release of Sisense Hunch which provides the ability to transform even the most massive data sets into a deep neural net which can be placed anywhere, even on an IoT device. AI Throughout.

Analytics 75

Analytics Data-driven Dashboards IoT 75

Sisense

MAY 14, 2019

I am incredibly proud and excited that Periscope Data is combining forces with Sisense in a merger that makes it possible to deliver the premier end-to-end BI and analytics platform that is unmatched in the industry. Harry and Tom had the vision to see a world where business was guided by deep and complex data-driven insights.

Data-driven 49

Data-driven Machine Learning Business Intelligence Consulting 49

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20