Astera

MAY 30, 2024

What Is Data Analytics? Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. Data Mining : Sifting through data to find relevant information.

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Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. This design philosophy was adapted from our friends at Fishtown Analytics.).

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Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. .

Data Quality 101

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Tableau

APRIL 18, 2022

A data fabric is an emerging data management design that allows companies to seamlessly access, integrate, model, analyze, and provision data. Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. .

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Data Pine

OCTOBER 25, 2022

With ‘big data’ transcending one of the biggest business intelligence buzzwords of recent years to a living, breathing driver of sustainable success in a competitive digital age, it might be time to jump on the statistical bandwagon, so to speak. of all data is currently analyzed and used. click for book source**.

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Data Pine

JANUARY 24, 2021

This genie (who we’ll call Data Dan) embodies the idea of a perfect data analytics platform through his magic powers. Now, with Data Dan, you only get to ask him three questions. The questions to ask when analyzing data will be the framework, the lens, that allows you to focus on specific aspects of your business reality.

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Actian

SEPTEMBER 17, 2019

Currently, three primary technologies work together to do the work of former data librarians and historians. Your company data is stored in databases and data warehouses. Legacy databases were good at capturing and maintaining a snapshot of data but often struggled with capturing and managing the change of data.

Artificial Intelligence 9

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Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

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The BAWorld

DECEMBER 23, 2023

Business Data Analyst Another distinct type is the Business Data Analyst, often seen working on data analytics projects. This role requires skills in data analytics, including knowledge of machine learning basics, artificial intelligence, and programming languages like Python.

Banking 52

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Astera

MAY 9, 2023

Six Stages of the Data Processing Cycle The data processing cycle outlines the steps that one needs to perform on raw data to convert it into valuable and purposeful information. Data Input Data input stage is the stage in which raw data starts to take an informational form.

Data Warehouse 52

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Sisense

OCTOBER 7, 2019

Today, the way to solve this challenge is by bringing in artificial intelligence and machine learning. Augmented analytics is the next iteration of business intelligence, where AI elements are incorporated into every phase of the BI process. The rise of cloud data warehouses has changed the way companies treat their data.

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Astera

APRIL 28, 2023

To address these challenges, approximately 44% of companies are planning to invest in artificial intelligence (AI) to streamline their data warehousing processes and improve the accuracy of their insights. AI is a powerful tool that goes beyond traditional data analytics.

E-Commerce 40

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Actian

SEPTEMBER 17, 2019

Currently, three primary technology shifts are combining to move beyond the capabilities and expected outcomes of Data Historian software. Modern Time-Series Databases capture multi-modal data. Outside of the OT domain, the rest of your company data is stored in standard databases and data warehouses.

Artificial Intelligence 40

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Actian

SEPTEMBER 12, 2019

Artificial Intelligence (AI) systems seem to be everywhere and for a good reason. Data persistence enables workflow continuity and tracking across multiple systems. Artificial Intelligence is arguably the most important technological development of the modern era.

Data Requirement 40

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Actian

SEPTEMBER 12, 2019

Artificial Intelligence (AI) systems seem to be everywhere and for a good reason. Data persistence enables workflow continuity and tracking across multiple systems. Artificial Intelligence is arguably the most important technological development of the modern era.

Data Requirement 8

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Astera

SEPTEMBER 20, 2023

It ensures businesses can harness the full potential of their data assets effectively and efficiently. It empowers them to remain competitive and innovative in an increasingly data-centric landscape by streamlining data analytics, business intelligence (BI) , and, eventually, decision-making.

Data Warehouse 52

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Astera

SEPTEMBER 20, 2023

It ensures businesses can harness the full potential of their data assets effectively and efficiently. It empowers them to remain competitive and innovative in an increasingly data-centric landscape by streamlining data analytics, business intelligence (BI) , and, eventually, decision-making.

Data Warehouse 52

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Astera

SEPTEMBER 28, 2023

It’s one of many ways organizations integrate their data for business intelligence (BI) and various other needs, such as storage, data analytics, machine learning (ML) , etc. ETL provides organizations with a  single source of truth  (SSOT) necessary for accurate data analysis. What is Reverse ETL?

Data Warehouse 52

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Actian

JULY 11, 2019

Efforts to standardize data models and interfaces have been largely unsuccessful due to the desire of some large players in the market to develop and defend closed technology ecosystems. Why operational technology data management may never be standardized. The biggest challenge to standardizing OT data management is managing change.

Data Management 40

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Actian

MAY 21, 2019

For many years, companies have been accumulating large amounts of data with an intuitive feeling that it has value and would be put to good use to make more informed business decisions. In this case, actionable business insights are the finished product you are seeking to provide to your data consumers.

Big Data 40

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Astera

JULY 13, 2023

The Role of Data Wrangling in Data Analytics Data analytics often produces a collection of informative reports, insightful visualizations, and illuminating graphs. These beautiful visualizations are the result of behind-the-scenes data wrangling.

Artificial Intelligence 40

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Data Pine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. If you’d like some resources in this area, we have posts on related business intelligence books and business intelligence podcasts you can use to start your research. Business Intelligence Job Roles.

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Actian

FEBRUARY 24, 2020

Continuous improvement, be it through process analysis and optimization or supported by machine learning and artificial intelligence, requires RPA vendors to aggregate distributed data in a centralized location for analysis and the harvesting of enterprise insights.

Digital Transformation 40

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Astera

MAY 6, 2024

It utilizes artificial intelligence to analyze and understand textual data. Best For: Businesses that require a wide range of data mining algorithms and techniques and are working directly with data inside Oracle databases. Cons: There’s a high learning curve for using Apache Mahout.

Data Mining 52

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The BAWorld

NOVEMBER 22, 2021

Top Data Analytics terms are explained in this article. Learn these to develop competency in Business Analytics. Data Analytics Terms & Fundamentals. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms. Also, see data visualization.

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Data Pine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. million searches per day and 1.2

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Astera

OCTOBER 28, 2024

Now, imagine if you could talk to your data warehouse; ask questions like “Which country performed the best in the last quarter?” Believe it or not, striking a conversation with your data warehouse is no longer a distant dream, thanks to the application of natural language search in data management.

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Astera

AUGUST 28, 2024

However, with the abundance of different types of data analysis tools in the market, what was supposed to be a simple task has become a complex undertaking. This article aims to simplify the process of finding the data analytics platform that meets your organization’s specific needs.

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Astera

SEPTEMBER 30, 2024

It refers to information or data assets moving from point A to B. In terms of data integration, this implies the movement of data from multiple sources, such as a database, to a destination, which could be your data warehouse optimized for business intelligence (BI) and analytics.

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Insight Software

MAY 1, 2023

Third-party data might include industry benchmarks, data feeds (such as weather and social media), and/or anonymized customer data. Four Approaches to Data Analytics The world of data analytics is constantly and quickly changing. The application thus becomes a vital information hub.

Embedded Analytics 52

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Insight Software

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.

IBM Maintenance 52

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Insight Software

AUGUST 13, 2024

We know it feels like all anyone talks about these days is artificial intelligence. Artificial intelligence (AI) and machine learning (ML) tools have been around for a while, but ChatGPT brought AI into the mainstream in ways that hadn’t been seen before. It’s everywhere – and for good reason.

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Insight Software

SEPTEMBER 25, 2024

Navigating the Future: Generative AI, Application Analytics, and Data Download Now Keeping up with AI Evolution In recent years, artificial intelligence (AI) has drastically changed. Before 2022, AI used machine learning capabilities to rapidly absorb data so that it could easily recognize trends, patterns, and outliers.

IBM Maintenance 52

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Insight Software

APRIL 24, 2024

In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your data analysis?

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