Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. The Benefits of Data Mesh. The mesh is highly secure.

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Data Management Government Data Warehouse Big Data 189

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.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

BizAcuity

JULY 13, 2021

Fraud Detection: AI records the data of users and their gambling activities and collectively determines cheating methods by flagging its suspicious occurrence and therefore, suspending accounts for further investigation. Data Enrichment/Data Warehouse Layer. Data Analytics Layer. Data Visualization Layer.

Data Warehouse 130

Data Warehouse Artificial Intelligence Data Analytics Data Analytics 130

Astera

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

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Data Warehouse Data Quality Big Data Predictive Analytics 52

Domo

JANUARY 7, 2025

Today inside Domo, AI agents are transforming how our customers operate , turning data into decisions and actions that drive real business value. In Domo, data, analytics, and AI dont just coexist; they converge. While these AI agents are designed to work efficiently, we also care about excellence in governance.

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IBM Support IBM Maintenance Artificial Intelligence Data Warehouse 75

Domo

MAY 24, 2021

To understand how to get there, let’s first look at why it’s been so complicated to leverage all your data. Your company likely has data integrations and pipelines in place to support using data analytics to answer business questions, discover relationships and correlations, and predict outcomes across key areas of your business.

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Government Data Architecture Business Intelligence Business Intelligence 136

Smart Data Collective

JULY 22, 2019

Microsoft Power BI transforms data into visuals, lets you explore and analyze any data easily, as well as share it with your colleagues. Built-in governance and security allow users to scale the service across practically any organizations. It can analyze practically any size of data. per month per one user.

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Business Intelligence Business Intelligence Visualization Real-time Data 259

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.

Data Warehouse 52

Data Warehouse Documentation Healthcare Data Management 52

ElegantJ BI

MAY 19, 2020

With Gartner and other technology research firms publishing reports and analysis about these trends, it is hard to believe that anyone working in technology (or in data science or analysis) would be in the dark (or skeptical), but apparently there are still a few people out there who need convincing! So, let’s go over this again.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Governance 130

Business Analysis Knowledge Share

MARCH 15, 2023

Understanding the key concepts of data warehousing, such as data integration, dimensional modeling, OLAP, and data marts, is vital for business analysts who are responsible for analyzing data and providing insights that drive business performance. What is Data Warehousing?

Big Data 52

Big Data Data Analytics Data Analytics Data Warehouse 52

The BAWorld

FEBRUARY 18, 2025

Power BI has become a go-to tool in the business intelligence (BI) and data analytics field, allowing companies to convert raw data into actionable reports and dashboards. Develops integration of Power BI with cloud and on-premise data systems. Managing data security and compliance. How would you do it with SQL?

Data Modelling 40

Data Modelling Data Warehouse Data Security Government 40

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

Actian

AUGUST 7, 2019

Over the past few years, we’ve seen an increasing trend of regional governments applying unique restrictions and controls on where data is stored and how it is managed for users and businesses in their jurisdiction. The EU and Japan have recently imposed some strict rules about data export. Data warehouses in the cloud.

Data Warehouse 40

Data Warehouse Data Mining Government Data Analytics 40

Actian

AUGUST 7, 2019

Over the past few years, we’ve seen an increasing trend of regional governments applying unique restrictions and controls on where data is stored and how it is managed for users and businesses in their jurisdiction. The EU and Japan have recently imposed some strict rules about data export. Data warehouses in the cloud.

Data Warehouse 8

Data Warehouse Data Mining Government Data Analytics 8

Tableau

APRIL 18, 2022

Data, security, and resource governance: Nurture data across its lifecycle with policies that remain consistent with every use. Ensure the behaves the way you want it to— especially sensitive data and access. Data integration. The analytics-first approach. Slow implementation of governance standards.

Data Quality 102

Data Quality Government Artificial Intelligence Data Warehouse 102

Tableau

APRIL 18, 2022

Data, security, and resource governance: Nurture data across its lifecycle with policies that remain consistent with every use. Ensure the behaves the way you want it to— especially sensitive data and access. Data integration. The analytics-first approach. Slow implementation of governance standards.

Data Quality 98

Data Quality Government Artificial Intelligence Data Warehouse 98

Inflexion Analytics

JULY 23, 2021

Both crop revenues and input costs are susceptible to the pricing gyrations that are inevitable in commodity markets—sometimes exacerbated by government interventions. But falling costs means that data and analytics tools will soon be accessible to the many. The data warehouse is the farm’s ‘single source of truth.’.

Big Data 52

Big Data Data Analytics Data Analytics Data Warehouse 52

Actian

FEBRUARY 13, 2020

Does your company have a real-time connected data warehouse where you can aggregate data flowing in from all of your IT systems together with streaming data from IoT, mobile, and SaaS services? Can you easily connect your on-premise, cloud, and multi-cloud systems to enable centralized analytics?

Data Warehouse 40

Data Warehouse Supply Chain Enterprise Architecture Digital Transformation 40

ElegantJ BI

NOVEMBER 16, 2016

If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. By providing a full suite of features with sophisticated functionality, and a true self-serve environment, the organization can encourage and support data democratization.

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Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

NOVEMBER 16, 2016

If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. By providing a full suite of features with sophisticated functionality, and a true self-serve environment, the organization can encourage and support data democratization.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

ElegantJ BI

NOVEMBER 16, 2016

If the value of the data, analysis and decision support is not persuasive, your business users will not adopt these business intelligence tools. Data Access. By providing a full suite of features with sophisticated functionality, and a true self-serve environment, the organization can encourage and support data democratization.

Data Discovery 130

Data Discovery Business Intelligence Business Intelligence Data Visualization 130

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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Astera

AUGUST 29, 2024

It enables easy data sharing and collaboration across teams, improving productivity and reducing operational costs. Identifying Issues Effective data integration manages risks associated with M&A. It includes: Identifying Data Sources involves determining the specific systems and databases that contain relevant data.

Data Governance 52

Data Governance Data Warehouse Data Quality Government 52

Sisense

AUGUST 4, 2021

Infusing intelligence everywhere is where Sisense shines, which is why in Q2 we’ve invested in bringing you Infusion Apps that leverage our brand new Extense Framework along with other features that allow you to explore new dimensions of your data. Analytics adoption has stalled; only infused analytics can help. Learn more.

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Actian

SEPTEMBER 30, 2019

In the prior three blogs from this series, we looked at i) maximizing the value of available data , ii) leveraging the right data for the right decision-making , and iii) identified key challenges to the adoption of cloud data warehouse solutions. Data governance and compliance needs.

Data Warehouse 40

Data Warehouse Data Architecture Data Analytics Data Analytics 40

Actian

SEPTEMBER 30, 2019

In the prior three blogs from this series, we looked at i) maximizing the value of available data , ii) leveraging the right data for the right decision-making , and iii) identified key challenges to the adoption of cloud data warehouse solutions. Data governance and compliance needs.

Data Warehouse 8

Data Warehouse Data Architecture Data Analytics Data Analytics 8

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

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Astera

SEPTEMBER 4, 2024

Data mesh was first presented as a concept by Zhamak Dehghani in 2019. It is a domain-oriented data architecture approach to decentralizing data analytics. Data mesh ensures the timely availability of data analytics to multiple teams, eliminating siloed data in the process.

Data Architecture 52

Data Architecture Data Governance Government Data Discovery 52

Data Pine

FEBRUARY 22, 2022

Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on. This should also include creating a plan for data storage services. CFOs and CMOs are good fits.

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Business Intelligence Business Intelligence Chief Data Officer Government 87

Astera

MAY 14, 2024

Metadata management Before proceeding, it’s essential to clarify that while both master data management (MDM) and metadata management are crucial components of data management and governance, they are two unique concepts and, therefore, not interchangeable. Data is only valuable if it is reliable.

Government 52

Government Data Governance Master Data Management Documentation 52

Cprime

MAY 4, 2023

Key Data Integration Use Cases Let’s focus on the four primary use cases that require various data integration techniques: Data ingestion Data replication Data warehouse automation Big data integration Data Ingestion The data ingestion process involves moving data from a variety of sources to a storage location such as a data warehouse or data lake.

Data Warehouse 52

Data Warehouse Big Data Finance Data Quality 52

Actian

NOVEMBER 26, 2019

The Challenges of Connecting Disparate Data Sources and Migrating to a Cloud Data Warehouse. Migrating to a cloud data warehouse makes strategic sense in the modern context of cloud services and digital transformation. Conceptually, it is easy to understand why you would want to move to a cloud data warehouse.

Data Warehouse 8

Data Warehouse Vision Digital Transformation Digital 8

Astera

APRIL 24, 2024

There are different types of data ingestion tools, each catering to the specific aspect of data handling. Standalone Data Ingestion Tools : These focus on efficiently capturing and delivering data to target systems like data lakes and data warehouses.

Data Warehouse 52

Data Warehouse Real-time Data Documentation Data Quality 52

Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

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Astera

NOVEMBER 27, 2023

It’s a method used to diagnose the data’s health by thoroughly examining its structure, content, and relationships. It ensures that the data is accurate, consistent, and unique before it’s used for ETL and data analytics. It can also highlight patterns, rules, and trends within the data.

Data Mining 52

Data Mining Data Quality Business Intelligence Data Governance 52

Astera

APRIL 7, 2023

An EDA includes these components: Data Governance – comprises of a set of policies, procedures, and guidelines for managing data across enterprise. Data Integration – the process of collecting and combining data from multiple data sources to create a unified data view.

Data Architecture 52

Data Architecture Supply Chain Data Governance Data Quality 52

Astera

APRIL 7, 2023

An EDA includes these components: Data Governance – comprises of a set of policies, procedures, and guidelines for managing data across enterprise. Data Integration – the process of collecting and combining data from multiple data sources to create a unified data view.

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