Smarten

APRIL 25, 2024

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics? There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

Rocket-Powered Data Science

JULY 19, 2023

I recently saw an informal online survey that asked users which types of data (tabular, text, images, or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

Data-driven 186

Data-driven Enterprise Analytics Machine Learning 186

Smarten

JANUARY 30, 2024

Self-Serve Data Preparation Transforms Business Users to Citizen Data Scientists! Data Scientists spend a lot of time gathering and preparing data for analysis, and that is time they could spend more productively performing tasks that add value and strategic direction. It’s simple.

Analytics 67

Analytics Data Quality Visualization Metadata 67

Cloudera

JUNE 3, 2022

Data scientists and machine learning engineers in enterprise organizations need to fully understand their data in order to properly analyze it, build models, and power machine learning use cases across their business. Data scientists are likely to use a variety of different tools to move through their processes.

Dashboards 88

Dashboards Visualization Machine Learning Data Science 88

Cloudera

JANUARY 6, 2021

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. Put Operations.

Machine Learning 131

Machine Learning Data Science Management Enterprise 131

Business Over Broadway

FEBRUARY 14, 2021

A recent survey by Kaggle revealed that data professionals used a variety of different ML algorithms in their work. On average, data professionals used two (median) algorithms. Machine learning algorithms are employed by data professionals to predict important outcomes as well as find patterns and structure in their data.

Machine Learning 106

Machine Learning Data Science Reporting Marketing 106

datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 88

Metrics Machine Learning Risk Statistics 88

Smarten

NOVEMBER 2, 2023

Three Factors to Ensure Success of a Citizen Data Scientist Initiative! Gartner analysts predict that, ‘…citizen data scientists will surpass data scientists in the amount of advanced analysis produced.’

Predictive Analytics 67

Predictive Analytics Analytics Visualization Reporting 67

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

DECEMBER 18, 2023

One of the largest sources of data is all around us—that is, geospatial data. Geographic information systems (GIS ) visualize and make sense of this data, helping people and businesses better understand the patterns and relationships of our world. Read more about the initiative here.

Internet of Things 106

Internet of Things IoT Forecasting Visualization 106

Smart Data Collective

AUGUST 22, 2019

Data science is one of the most promising career paths of the 21st-century. Over the past year, job openings for data scientists increased by 56%. People that pursue a career in data science can expect excellent job security and very competitive salaries. Data scientists typically dress in nice button up shirts and jeans.

Data Science 83

Data Science Big Data Publishing Technology 83

Cloudera

MARCH 2, 2023

Recently, we announced enhanced multi-function analytics support in Cloudera Data Platform (CDP) with Apache Iceberg. Iceberg is a high-performance open table format for huge analytic data sets. This enables you to maximize utilization of streaming data at scale. The Catalog Type should be set to Hive.

Snapshot 112

Snapshot Data Processing Metadata Management 112

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

Smarten

MARCH 7, 2024

Auto Insights frees business users and reduces the time and skills required to produce accurate, clear results, quickly and dependably, using machine learning that frees the business user to collect and analyze data with the guided assistance of a ‘smart’ solution. Instead, the user will simply select the dataset to be analyzed.

Analytics 67

Analytics Predictive Modeling Machine Learning Visualization 67

IBM Big Data Hub

JANUARY 5, 2024

From securing everyday personal messages and the authentication of digital signatures to protecting payment information for online shopping and even guarding top-secret government data and communications—cryptography makes digital privacy possible. This enabled a new form of encryption called asymmetric key algorithms.

Consulting 101

Consulting Technology Risk Publishing 101

Smarten

FEBRUARY 17, 2022

What Determines the Success of a Citizen Data Scientist Initiative? By now, every wise business team has acknowledged the advent of digital transformation and the transformation of business users into Citizen Data Scientists. This prediction reflects the shift toward the use of data within the enterprise, and rightly so.

Predictive Modeling 76

Predictive Modeling Digital Transformation Enterprise Data Science 76

Alation

OCTOBER 7, 2021

Jason McVay is a data scientist at Indigo Ag, an agriculture-tech company headquartered in Massachusetts. In this essay, Jason reflects on the value of thinking spatially about data, showing how his experience as a graduate student influences his role as a data scientist today. The rise of spatial data.

Data Lake 98

Data Lake Visualization Data Science Digital Transformation 98

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

IBM Big Data Hub

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements.

Machine Learning 72

Machine Learning Optimization Unstructured Data Sales 72

Smarten

MAY 31, 2022

When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Provide the right predictive analytics tools to transition business users into Citizen Data Scientists and achieve the kind of results this type of initiative can deliver.’.

Predictive Analytics 67

Predictive Analytics Analytics Predictive Modeling Prescriptive Analytics 67

TDAN

OCTOBER 5, 2021

Data is the raw material for any type of analytics – whether it is related to historical analysis presented in reports and dashboards by business analysts, or predictive analysis that involves building a model by data scientists that anticipates an event or behavior that has not yet occurred.

Data Science 69

Data Science Dashboards Reporting Modeling 69

Smarten

APRIL 18, 2023

Digital Transformation and Citizen Data Scientists Go Hand-in-Hand! Gartner predicts that, ‘50% of organizations will adopt modern data quality solutions to better support their digital business initiatives.’ The human resource component is the active ingredient that makes it all work!

Digital Transformation 52

Digital Transformation Predictive Modeling Data Quality Enterprise 52

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

Smart Data Collective

SEPTEMBER 23, 2020

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse. billion by 2030.

Data Lake 106

Data Lake Data Warehouse Unstructured Data Big Data 106

Cloudera

FEBRUARY 21, 2023

SQL Stream Builder (SSB) is a versatile platform for data analytics using SQL as a part of Cloudera Streaming Analytics, built on top of Apache Flink. It enables users to easily write, run, and manage real-time continuous SQL queries on stream data and a smooth user experience. What is a data transformation?

Data Transformation 107

Data Transformation Data Processing Data Collection Publishing 107

AWS Big Data

APRIL 24, 2024

EMR Studio is an integrated development environment (IDE) that makes it straightforward for data scientists and data engineers to develop, visualize, and debug analytics applications written in PySpark, Python, and Scala. Now you can use a dataset and visualize your data. Choose Save changes. option("header", "true").option("inferSchema",

Interactive 80

Interactive Visualization Big Data Management 80

Domino Data Lab

JULY 19, 2021

One of the primary challenges of any ML/AI project is transitioning it from the hands of data scientists in the develop phase of the data science lifecycle into the hands of engineers in the deploy phase. Where in the life cycle does data scientists’ involvement end? Data engineers assist by providing clean data.

Enterprise 85

Enterprise Data Science Testing Modeling 85

Ontotext

FEBRUARY 1, 2024

For example, the method for managing multilingual taxonomies became massively simpler (once concept could now hold multiple language labels), resulting in huge cost savings compared with the previous data model. The widespread adoption of RDF as a semantic data model transformed simple taxonomies into extensible and expressive ontologies.

Enterprise 59

Enterprise Management Metadata Modeling 59

IBM Big Data Hub

SEPTEMBER 6, 2023

From customized content creation to task automation and data analysis, AI has seemingly endless applications when it comes to marketing, but also some potential risks. Here are some key definitions, benefits, use cases and finally a step-by-step guide for integrating AI into your next marketing campaign. What is AI marketing?

Marketing 86

Marketing Technology Advertising ROI 86

Smarten

FEBRUARY 16, 2023

Taking on the Citizen Data Scientist Role: What’s in it for Me? As a team member within a business environment, you may be aware of the term ‘Citizen Data Scientist.’ ” ‘Transforming business users into Citizen Data Scientist can provide numerous benefits to you as a Citizen Data Scientist candidate.’

Prescriptive Analytics 52

Prescriptive Analytics Statistics Consulting Metrics 52

Smarten

NOVEMBER 8, 2022

Planning Will Help Your Business Get the Most Out of a Citizen Data Scientist Strategy! Technology research firm Gartner has predicted that 50% of data scientist activities will be automated by artificial intelligence, easing the acute talent shortage. A definition and discussion of Predictive Analytics.

Strategy 52

Strategy Digital Transformation Predictive Analytics Risk 52

Smarten

AUGUST 5, 2022

The technology research firm, Gartner, states that, ‘50% of data scientist activities will be automated by artificial intelligence, easing the acute talent shortage.’. Predictive analytics is comprised of sophisticated analytical methodologies that allow businesses to predict future outcomes based on historical data.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Analytics Forecasting 52

Smarten

JANUARY 18, 2023

Include Citizen Data Scientists in Your Continuous Improvement Program and Make it Happen! A Continuous Improvement program can and should include a Citizen Data Scientist initiative.’ If the Citizen Data Scientist initiative is implemented correctly, it will naturally and organically contribute to continuous improvement.

Key Performance Indicator 52

Key Performance Indicator Prescriptive Analytics Business Objectives Measurement 52

Cloudera

APRIL 10, 2021

When working on complex, or rigorous enterprise machine learning projects, Data Scientists and Machine Learning Engineers experience various degrees of processing lag training models at scale. While model training on small data can typically take minutes, doing the same on large volumes of data can take hours or even weeks.

Machine Learning 61

Machine Learning Modeling Cost-Benefit Data Science 61

IBM Big Data Hub

DECEMBER 5, 2022

DSCE works seamlessly for both data scientist and machine learning operations (ML-Ops) engineers’ personas. For example, data scientist, Miles wants to customize an emotion classification model to discover what makes customers happiest. Medium Blog: What are Watson Libraries? Embark on a task-based journey.

Modeling 57

Modeling Digital Transformation Interactive Software 57