Insight Software

JANUARY 20, 2021

It’s hard to imagine taking that step, though, without first getting a handle on the organization’s existing data. Reining in all of this complexity is a critical first step in the process of creating a strategically relevant data analytics program. First, you must make all of those data available in a centralized repository.

Data Management 95

Data Management Data Analytics Data Analytics E-Commerce 95

Smart Data Collective

JULY 22, 2019

Zoho Analytics is popular business intelligence, reporting, and analytics software from the creators of a popular web-based solution Zoho Office. Zoho Analytics is able to integrate data from a wide range of sources and turn it into a visually appealing and easy to comprehend reports for marketing, sales and other departments.

Business Intelligence 259

Business Intelligence Business Intelligence Visualization Real-time Data 259

Sisense

MAY 28, 2019

2019 can best be described as an era of modern cloud data analytics. Convergence in an industry like data analytics can take many forms. We have seen industry rollups in which firms create a collection of analytical tools under one brand. They also have the resources to acquire a technology that meets this need.

Data Analytics 89

Data Analytics Data Analytics IBM Support Data Warehouse 89

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

Data Warehouse 130

Data Warehouse Artificial Intelligence Data Analytics Data Analytics 130

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. We need to start where every great AI solution begins: data. So, what sets AI agents built in Domo apart?

IBM Support 75

IBM Support IBM Maintenance Artificial Intelligence Data Warehouse 75

BizAcuity

MAY 16, 2022

The more effectively a company uses data, the better it performs. As a data analytics company, we have been observing a trend among certain large enterprises who are looking for real-time data streaming for analytics. Data mining. Visual Analytics and Data Visualization.

Business Intelligence 130

Business Intelligence Business Intelligence Data Mining Data Warehouse 130

Astera

NOVEMBER 14, 2023

If you have had a discussion with a data engineer or architect on building an agile data warehouse design or maintaining a data warehouse architecture, you’d probably hear them say that it is a continuous process and doesn’t really have a definite end. What do you need to build an agile data warehouse?

Data Warehouse 52

Data Warehouse Agile Data Modelling Data Quality 52

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Good Visualization Options.

IBM Support 130

IBM Support IBM cost IBM Maintenance Big Data 130

Astera

DECEMBER 21, 2022

For this reason, most organizations today are creating cloud data warehouse s to get a holistic view of their data and extract key insights quicker. What is a cloud data warehouse? Moreover, when using a legacy data warehouse, you run the risk of issues in multiple areas, from security to compliance.

Data Warehouse 52

Data Warehouse Supply Chain Business Intelligence Business Intelligence 52

Astera

MAY 31, 2024

Data Science vs. Data Analytics Organizations increasingly use data to gain a competitive edge. Two key disciplines have emerged at the forefront of this approach: data science vs data analytics. In contrast, data science enables you to create data-driven algorithms to forecast future outcomes.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

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.

Government 136

Government Data Architecture Business Intelligence Business Intelligence 136

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.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

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**.

Business Intelligence 117

Business Intelligence Business Intelligence Big Data Data Mining 117

Analysts Corner

OCTOBER 26, 2023

This data must be cleaned, transformed, and integrated to create a consistent and accurate view of the organization’s data. Data Storage: Once the data has been collected and integrated, it must be stored in a centralized repository, such as a data warehouse or a data lake.

Business Intelligence 130

Business Intelligence Business Intelligence Supply Chain Data Mining 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. Creates data models, streamlines ETL processes, and enhances Power BI performance. ollaborates with analysts and IT teams to provide smooth data flow.

Data Modelling 40

Data Modelling Data Warehouse Data Security Government 40

Domo

JULY 28, 2022

With more than 2,000 issued patents for advances in technology, the cutting-edge, multi-national company builds core innovations in connectivity, modeling, and data analytics for customers in agriculture, construction, and transportation. And we wanted to bring our own data engineering group. And for good reason.

Embedded Analytics 98

Embedded Analytics Data Warehouse Digital Transformation Data Architecture 98

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.

Data Visualization 126

Data Visualization Data Analytics Data Analytics Data Quality 126

BizAcuity

MAY 10, 2022

2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. Microsoft also releases Power BI, a data visualization and business intelligence tool. There is Alibaba Cloud, Turbonomic, Terremark etc.

IBM cost 130

IBM cost IBM Support Cloud Computing Data Warehouse 130

Sisense

JANUARY 15, 2021

The modern data team has gained traction in large part thanks to the startups in Silicon Valley that have put an emphasis on collecting, analyzing, and commoditizing data. These younger companies have invested in talent with specific data science skills, particularly with code-driven data analytics.

Skillset 75

Skillset Data Warehouse Data Modelling Business Intelligence 75

BizAcuity

MARCH 28, 2022

No wonder casinos have full-fledged data analytics teams both in-house and outsourced. The data points related to users/players reside across multiple channels and platforms i.e. websites, apps, CRMs, Ad networks, and financial software.

User Experience 130

User Experience Data Warehouse Planning Data Visualization 130

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.).

Data Modelling 84

Data Modelling Big Data Data Analytics Data Analytics 84

Sisense

AUGUST 22, 2019

This means that every exercise is a complex challenge of data engineering, and even when the work is done the results are removed from your visualization and reporting solutions. What’s been missing is a way to natively integrate Python and R with the rest of the data analytics stack. No more data engineering!

Predictive Analytics 73

Predictive Analytics Data Warehouse Business Intelligence Business Intelligence 73

Data Pine

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.

IBM cost 117

IBM cost Data Warehouse Business Intelligence Business Intelligence 117

Astera

APRIL 27, 2023

These are various sources, like databases or third-party apps such as Salesforce and HubSpot, that contain raw data stored in an unorganized manner i.e., unstructured data Data pipeline tools The ELT data pipeline tools gather and move data from the data sources. What Are the Benefits of a Modern Stack?

Data Warehouse 52

Data Warehouse Big Data Data Analytics Data Analytics 52

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.

Data Warehouse 52

Data Warehouse Data Mining Artificial Intelligence Visualization 52

Actian

JANUARY 23, 2020

The challenge with analyzing and visualizing social relationships is that the underlying data doesn’t match well with the relational data structures that most data warehouses are designed around. Meaning difficult data problems can be analyzed more quickly, giving leaders the answers they seek fast.

Visualization 40

Visualization Data Warehouse Big Data Digital 40

Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Data integration. Orchestration.

Data Quality 102

Data Quality Government Artificial Intelligence Data Warehouse 102

Astera

MAY 25, 2023

Unlocking the Potential of Amazon Redshift Amazon Redshift is a powerful cloud-based data warehouse that enables quick and efficient processing and analysis of big data. Amazon Redshift can handle large volumes of data without sacrificing performance or scalability. What Is Amazon Redshift? 

Data Warehouse 52

Data Warehouse Data Modelling Banking Real-time Data 52

Tableau

APRIL 18, 2022

Shine a light on who or what is using specific data to speed up collaboration or reduce disruption when changes happen. Data modeling. Leverage semantic layers and physical layers to give you more options for combining data using schemas to fit your analysis. Data preparation. Data integration. Orchestration.

Data Quality 98

Data Quality Government Artificial Intelligence Data Warehouse 98

Astera

JANUARY 11, 2024

These challenges include: Legacy Systems: Outdated systems make it difficult to get the best data into your data warehouse. Divergent data sources can lead to conflicting information, undermining accuracy and reliability. A well-planned selection process ensures compatibility, scalability, and security.

Data Warehouse 52

Data Warehouse Finance Visualization Planning 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.

Data Warehouse 52

Data Warehouse User Experience Government Innovation 52

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.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Whizlabs

JUNE 27, 2021

The subdomains for this module are: Describing the different types of core data workloads. Describing the data analytics core concepts. Describe How to Work with Relational Data on Azure. Cover the subdomains of this module, as you can expect a good lot of questions from this section: Describing the Analytics Workloads.

Documentation 104

Documentation Data Warehouse Data Visualization Data Analytics 104

Inflexion Analytics

AUGUST 24, 2020

The Azure cloud platform provides powerful, yet easy to use cloud-based tools for data transformation , data analytics and data science. This blog provides a brief run through of some of the features of the Azure tools for data analysts and data scientists. Azure Options for Data Analytics.

Data Warehouse 52

Data Warehouse Data Analytics Data Analytics Big Data 52

Sisense

MARCH 14, 2021

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data Data Analytics Data Analytics Supply Chain 52

Data Pine

MARCH 31, 2022

To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools. Front-end analytical and business intelligence skills are geared more towards presenting and communicating data to others. b) If You’re Already In The Workforce.

Business Intelligence 95

Business Intelligence Business Intelligence Data Visualization Visualization 95