Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. Almost every modern organization is now a data-generating machine. or “how often?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

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. Data Lineage Tells an Important Origin Story. Who are the data owners?

Data Governance 131

Data Governance Key Performance Indicator Metadata Digital Transformation 131

DataRobot

APRIL 19, 2021

Data Scientists Are AI Experts. But for more complex business decisions, including those that use less structured data, we have artificial intelligence systems. Data scientists train the algorithms using datasets that contain curated learning examples. Data Scientists and Error Detection. Not All AI Is Trustworthy.

Machine Learning 52

Machine Learning Visualization Data-driven Data Science 52

O'Reilly on Data

APRIL 19, 2021

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. The second-most significant barrier was the availability of quality data. Relatively few respondents are using version control for data and models. Respondents.

Enterprise 360

Enterprise Risk Modeling Manufacturing 360

Ontotext

JUNE 22, 2023

Another problem in drug development is that although companies gather a lot of data from multiple databases, they struggle to derive key insights about safety, drugability, etc. They need some kind of compass to find their way in the data jungle and identify information that is useful and relevant to their specific use case.

Metrics 52

Metrics Statistics Visualization Metadata 52

Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics).

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Sisense

JUNE 8, 2020

Every company is becoming a data company. In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

Octopai

JUNE 26, 2020

We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Steve needed a robust and automated metadata management solution as part of his organization’s data governance strategy. Enterprise data governance. Metadata in data governance. Metadata is essentially the ‘data about data.’

Metadata 98

Metadata Data Governance Enterprise Reporting 98

FineReport

APRIL 24, 2024

Learn Data Visualization Understanding the Importance of Visualizing Data Data visualization is a powerful tool for conveying complex information in a clear and impactful manner. Understanding the principles of effective bar chart design is crucial for conveying information accurately and compellingly.

Visualization 52

Visualization Dashboards Interactive Data-driven 52

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. Data visualization: painting a picture of your data.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. The power of the data lake lies in the fact that it often is a cost-effective way to store data.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. There are four groups of data that are naturally siloed: Structured data (e.g., Transaction and pricing data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

Ontotext

SEPTEMBER 15, 2020

What Makes a Data Fabric? Data Fabric’ has reached where ‘Cloud Computing’ and ‘Grid Computing’ once trod. Data Fabric hit the Gartner top ten in 2019. This multiplicity of data leads to the growth silos, which in turns increases the cost of integration. It is a buzzword.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

FineReport

MAY 30, 2024

In today’s data-driven world, the data visualization specialist plays a pivotal role in transforming complex information into visually appealing formats. The demand for skilled professionals in this field is rapidly increasing as businesses rely more on data for decision-making and operations.

Visualization 52

Visualization Dashboards KPI Reporting 52

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

MARCH 25, 2024

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

Data Lake 102

Data Lake Unstructured Data Management Snapshot 102

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse.

Data Lake 84

Data Lake Data Warehouse Sales Data-driven 84

AWS Big Data

AUGUST 15, 2024

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.

Data Quality 105

Data Quality Visualization Metadata Key Performance Indicator 105

CDW Research Hub

APRIL 28, 2020

As businesses strive to become modern data-driven organizations, many are drawn to the value that a data platform in the cloud can provide. Cloud data platforms provide the speed, performance and scalability that is required to handle an exponential growth in volume of data.

Data-driven 52

Data-driven Analytics Consulting ROI 52

datapine

MAY 27, 2020

In recent years, analytical reporting has evolved into one of the world’s most important business intelligence components, compelling companies to adapt their strategies based on powerful data-driven insights. No more sifting through droves of spreadsheets, no more patchwork data analysis, and reporting methods.

Reporting 245

Reporting Analytics Dashboards Sales 245

Ontotext

FEBRUARY 26, 2024

This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. and “What is the financial impact?”.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

datapine

APRIL 28, 2023

Table of Contents 1) What Are Data Types? 2) The Need For Data Types 3) List Of Common Data Types a) Primitive Data Types b) Composite Data Types c) Abstract Data Types In our digitally-driven age, data is permeating every industry and business function at an increasing pace.

Data-driven 200

Data-driven Reporting Visualization Interactive 200

Jet Global

FEBRUARY 6, 2024

The landscape of business intelligence (BI) is undergoing a metamorphosis, demanding solutions that transcend static reports and siloed data. Hidden patterns in your data are illuminated in real-time, fostering intuitive, interactive exploration that unlocks the true narrative within your numbers. Gone are the days of cumbersome BI 1.0

Dashboards 52

Dashboards Visualization Data-driven Reporting 52

FineReport

DECEMBER 27, 2021

Dashboards and visualizations are the primary user interfaces of many tools and platforms. Business intelligence is the collection, storage, and analysis of data from firm activities to create a holistic perspective of a business. The data is managed, secure and tested for accuracy. Learn more about Self-service BI.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

FineReport

JULY 18, 2022

In an era full of data, data analysis allows us to discover the most useful information and make more scientific decisions for business operations. Data analysis tools are widely used by data analysts as well as non-professional business people to achieve better performance and higher efficiency. FineRepor t.

Forecasting 52

Forecasting Dashboards Statistics Visualization 52

CIO Business Intelligence

MAY 10, 2022

Customer data platform defined. A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. Customer data platform benefits. Types of CDPs.

Advertising 120

Advertising Interactive Marketing Structured Data 120

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive. Understanding how data becomes insights.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Ontotext

MAY 18, 2020

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

AWS Big Data

MARCH 26, 2024

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.

Data Strategy 76

Data Strategy Strategy Data Warehouse Prescriptive Analytics 76

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. And so will your data. You know the story well: you have a ton of data and need fast access to the right data. Building an efficient solution for data storage and processing is becoming more than just a back-office or IT challenge. Benefits of a Data Lake.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Juice Analytics

MARCH 27, 2021

We’ve found 10 of the best options to automate and update data for recurring presentations. The Challenge Let’s say you need to produce the same presentation month after month, updating the data each time. The presentation is basically the same, you simply want to swap out the underlying data. Efficiency. Cost: $29/user/month.

Reporting 122

Reporting Visualization Interactive Software 122

Cloudera

JULY 26, 2021

With this first article of the two-part series on data product strategies, I am presenting some of the emerging themes in data product development and how they inform the prerequisites and foundational capabilities of an Enterprise data platform that would serve as the backbone for developing successful data product strategies.

Strategy 119

Strategy Data Science Unstructured Data Marketing 119

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 60

Data Warehouse Unstructured Data Analytics Visualization 60

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

AWS Big Data

DECEMBER 21, 2023

This is a guest post co-written by Alex Naumov, Principal Data Architect at smava. smava believes in and takes advantage of data-driven decisions in order to become the market leader. smava believes in and takes advantage of data-driven decisions in order to become the market leader.

Data Lake 101

Data Lake Data Warehouse B2B Data-driven 101

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52