Dataversity

JULY 17, 2023

For data-driven organizations, this leads to successful marketing, improved operational efficiency, and easier management of compliance issues. However, unlocking the full potential of high-quality data requires effective Data Management practices.

Data Requirement 130

Data Requirement Data Management Data Quality Data Governance 130

Dataversity

DECEMBER 16, 2022

Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements. 2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning.

Data Requirement 130

Data Requirement Artificial Intelligence 130

BizAcuity

APRIL 19, 2019

Only, the data required to do this is not so easily available. But there are ways businesses can solve this. That too, efficiently. Think about it, using advanced technologies, we can analyse the users’ behaviour, preferences, actions and so much more.

Data Mining 189

Data Mining Real-time Data Data Analytics Data Analytics 189

Smart Data Collective

NOVEMBER 6, 2019

Look at your website dashboard and see which blog posts have received the most traffic. This is an organic approach to building your brand that you can improve with the data you collect from your customers. Because they specialize in this aspect of marketing, they have more data, resources, and knowledge that you have.

Big Data 133

Big Data Digital Data Requirement 133

BizAcuity

SEPTEMBER 30, 2019

We saw in our earlier blog that businesses today are deciding between cloud-based deployments and on premise solutions. Clarify your requirements and align to your organization needs – Ensure that you are very clear with your data requirements.

Data Governance 140

Data Governance Government Cloud Computing Monitoring 140

Domo

MAY 30, 2024

This not only improves your data but also helps cultivate a culture of quality across your organization. Celebrating these contributions can boost morale and encourage a proactive approach to data management. Regularly review your data practices and stay updated on solutions for improving your data’s quality and security.

Data Quality 105

Data Quality Data Governance Government Data Security 105

ElegantJ BI

DECEMBER 11, 2019

This analytical agility will help them to see data clearly and gain insight and, while these tools may not produce 100% accuracy in the hands of a business users, there are many times throughout the work day where users need good, solid information but do NOT need strategic, analytical information that is 100% accurate.

Data Quality 130

Data Quality Agile Innovation Visualization 130

ElegantJ BI

DECEMBER 11, 2019

This analytical agility will help them to see data clearly and gain insight and, while these tools may not produce 100% accuracy in the hands of a business users, there are many times throughout the work day where users need good, solid information but do NOT need strategic, analytical information that is 100% accurate.

Data Quality 130

Data Quality Agile Innovation Visualization 130

Sisense

AUGUST 14, 2020

In the case of a stock trading AI, for example, product managers are now aware that the data required for the AI algorithm must include human emotion training data for sentiment analysis. Artificial intelligence is transforming products in surprising and ingenious ways.

Healthcare 98

Healthcare Cybersecurity Predictive Analytics Artificial Intelligence 98

GAVS Technology

NOVEMBER 5, 2024

Human Error: Mistakes such as accidental data sharing or configuration errors that unintentionally expose data, requiring corrective actions to mitigate impacts. Data Theft: Unauthorized acquisition of sensitive information through physical theft (e.g., stolen devices) or digital theft (hacking into systems).

Cybersecurity 52

Cybersecurity Healthcare Monitoring Data Security 52

BizAcuity

SEPTEMBER 30, 2019

We saw in our earlier blog “ How to Choose Between Cloud-based and On-premise solutions ” that businesses today are deciding between cloud-based deployments and on-premise solutions. Clarify your requirements and align to your organization needs – Ensure that you are very clear with your data requirements.

Data Governance 113

Data Governance Government Cloud Computing Monitoring 113

ElegantJ BI

OCTOBER 1, 2020

But, businesses do not have the time or budget to provide unlimited IT resources and the fast pace of business and market changes has made it difficult to satisfy the day-to-day data requirements of business users.

Data Discovery 130

Data Discovery Data Warehouse Business Intelligence Business Intelligence 130

Juice Analytics

MARCH 11, 2021

Part 2: Development If “ Data is the Bacon of Business ” (TM), then customer reporting is the Wendy’s Baconator. In a recent blog post , we described the differences between customer reporting and data products. Those differences result in some very different functional requirements.

Product Management 128

Product Management Product Management Vision Healthcare 128

BizAcuity

SEPTEMBER 30, 2019

We saw in our earlier blog “ How to Choose Between Cloud-based and On-premise solutions ” that businesses today are deciding between cloud-based deployments and on premise solutions. Clarify your requirements and align to your organization needs – Ensure that you are very clear with your data requirements.

Data Governance 100

Data Governance Government Cloud Computing Monitoring 100

BizAcuity

SEPTEMBER 30, 2019

We saw in our earlier blog “ How to Choose Between Cloud-based and On-premise solutions ” that businesses today are deciding between cloud-based deployments and on premise solutions. Clarify your requirements and align to your organization needs – Ensure that you are very clear with your data requirements.

Data Governance 100

Data Governance Government Cloud Computing Monitoring 100

The BAWorld

MARCH 13, 2024

This blog dives into the top 10 most valuable business analysis techniques, equipping you to navigate complex challenges and deliver game-changing solutions. It ensures data consistency, accessibility, and integrity, facilitating efficient data storage, retrieval, and analysis.

Business Analysis 52

Business Analysis Business Analysis Backlog Management Process Modelling 52

Data Pine

MAY 2, 2023

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? The post 10 Examples of How Big Data in Logistics Can Transform The Supply Chain appeared first on BI Blog | Data Visualization & Analytics Blog | datapine.

Supply Chain 110

Supply Chain Logistics Big Data Customer Experience 110

Domo

DECEMBER 5, 2017

Real-time data requires agile execution Real-time data is only as helpful as your ability to execute on it quickly. Following the example of companies like Amazon and Freddy’s, data-driven success will be increasingly defined by how organizations turn real-time data into real-time decisions and actions.

Real-time Data 52

Real-time Data Agile User Experience Data Requirement 52

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. Qualitative data benefits: Unlocking understanding.

Visualization 98

Visualization Data Warehouse Innovation Predictive Analytics 98

BizAcuity

APRIL 1, 2023

Among other differences between the two options, data storage is a main factor – depending on the data requirement, you can choose which option of the tool to use. With a Power BI Pro license, you can upload up to 10 GB of data to the Power BI Cloud.

Data Modelling 130

Data Modelling Data Requirement 130

BizAcuity

SEPTEMBER 21, 2022

Among other differences between the two options, data storage is a main factor – depending on the data requirement, you can choose which option of the tool to use. With a Power BI Pro license, you can upload up to 10 GB of data to the Power BI Cloud.

Data Modelling 130

Data Modelling Data Requirement 130

Inflexion Analytics

APRIL 15, 2024

In this blog post, we’ll dive deep into the world of LLMs, exploring what makes them tick, why they matter, and how they’re reshaping industries across the board. Data Efficiency: LLMs require relatively small amounts of domain-specific data to fine-tune. What Are LLMs?

Artificial Intelligence 52

Artificial Intelligence Documentation Digital Innovation 52

Inflexion Analytics

APRIL 15, 2024

In this blog post, we’ll dive deep into the world of LLMs, exploring what makes them tick, why they matter, and how they’re reshaping industries across the board. Data Efficiency: LLMs require relatively small amounts of domain-specific data to fine-tune. What Are LLMs?

Artificial Intelligence 52

Artificial Intelligence Documentation Digital Innovation 52

Sisense

AUGUST 11, 2019

The sheer quantity and scope of data produced and stored by your company can make it incredibly hard to peer through the number-fog to pick out the details you need. This is where Business Analytics (BA) and Business Intelligence (BI) come in: both provide methods and tools for handling and making sense of the data at your disposal.

Business Intelligence 75

Business Intelligence Business Intelligence Data Mining Predictive Analytics 75

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Use by business units, departments or specific roles within the organization that have a need to analyze and report and require high quality data and good performance. Advantages: Can provide secured access to data required by certain team members and business units.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Use by business units, departments or specific roles within the organization that have a need to analyze and report and require high quality data and good performance. Advantages: Can provide secured access to data required by certain team members and business units.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

ElegantJ BI

SEPTEMBER 30, 2021

Suitable For: Use by business units, departments or specific roles within the organization that have a need to analyze and report and require high quality data and good performance. Advantages: Can provide secured access to data required by certain team members and business units.

Data Management 130

Data Management Data Warehouse Government Data Governance 130

Whizlabs

DECEMBER 13, 2020

The configuration insights will be an important aspect of DevOps trends empowering DevOps teams with data required for making informed decisions. Furthermore, businesses could also require the ability to control their releases to the end-users. The post Upcoming DevOps Trends for 2021 appeared first on Whizlabs Blog.

Monitoring 98

Monitoring Digital Transformation Product Management Product Management 98

Sisense

FEBRUARY 10, 2021

In order to do this, my team uses data to identify problem areas and potential issues for our customers (ideally before they happen). This presented the first challenge for our product team in building Cascade Insight: What is the data that is most important to capture?

Skillset 52

Skillset Data Requirement Data Quality Documentation 52

Astera

MARCH 26, 2023

But managing this data can be a significant challenge, with issues ranging from data volume to quality concerns, siloed systems, and integration difficulties. In this blog, we’ll explore these common data management challenges faced by insurance companies.

Documentation 52

Documentation Data Quality Data Warehouse Data Management 52

The BAWorld

NOVEMBER 24, 2023

As the volume and complexity of data increase, DA will become increasingly important in managing the digital age’s difficulties and opportunities. The post Fundamentals of Data Analytics appeared first on Business Analysis Blog.

Data Analytics 52

Data Analytics Data Analytics E-Commerce Predictive Analytics 52

Astera

APRIL 28, 2023

Final Verdict: Intelligent Systems are Changing the Game Intelligent systems are revolutionizing data management by providing new and innovative ways to analyze, process, and interpret vast amounts of data.

Data Management 93

Data Management Artificial Intelligence Predictive Analytics Data Quality 93

Domo

MARCH 24, 2020

The volume of data required to make these decisions adds increasing levels of complexity. The post 3 Hurdles to Successful Marketing—and How to Clear Them first appeared on Blog. In 2020, it won’t be the case of looking through simple linear reports.

Digital 52

Digital Government Vision Customer Experience 52

Astera

SEPTEMBER 25, 2024

Let’s find out in this blog. Airbyte is an open-source data integration platform that allows organizations to easily replicate data from multiple sources into a central repository. Focus on data security with certifications, private networks, column hashing, etc. Hevo Data Hevo Data is a no-code data pipeline tool.

Real-time Data 52

Real-time Data Data Warehouse Documentation Monitoring 52

The BAWorld

DECEMBER 6, 2023

Consider pursuing certifications to validate your understanding of key data analysis tools and methodologies, enhancing your credibility among potential employers. Step 2: Obtaining essential skills Data analysts play a crucial role in extracting meaningful insights from data, requiring a blend of technical and analytical skills.

Data Analytics 52

Data Analytics Data Analytics Artificial Intelligence Visualization 52

Astera

DECEMBER 22, 2022

Enterprises will soon be responsible for creating and managing 60% of the global data. Traditional data warehouse architectures struggle to keep up with the ever-evolving data requirements, so enterprises are adopting a more sustainable approach to data warehousing. Technical Assets .

Data Warehouse 52

Data Warehouse IBM Maintenance IBM Support Data Architecture 52

Astera

APRIL 3, 2023

With the need for access to real-time insights and data sharing more critical than ever, organizations need to break down the silos to unlock the true value of the data.

IBM Maintenance 52

IBM Maintenance IBM cost Data Security IBM Support 52