data

Traditional BI Buzzwords for Modern Data Teams

About a year into Chartio, we’d moved into our first real office in the Founder’s Den. Another Denizen came by and said something to the effect of “Oh, you guys are in the BI space…” and then proceeded to drop about a dozen buzz words, only a couple of which I knew. I’d interviewed almost 100 companies about how their data processes and needs but at that point I realized I’d completely missed researching any vendors of the traditional BI market and the incredible amount of jargon that that community comes with.

As it turns out BI is an incredibly jargon filled industry as a result of it being historically so fragmented, with the largest players owning less than 10% of the market [1]. These giant pieces of software took months to install and integrate so trials were few and far between. Deals were won by one sales and marketing

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Data, Business Intelligence Lead B2B VC Roundup

In a venture capital slowdown, any investment round is a win.

This week’s look at the latest funding for B2B FinTech and other startups showcases an investor appetite for security, data and business intelligence, with nearly $63.5 million in fresh investment for the industry. PYMNTS rounds up the latest deals below.

Whistic

Focused on mitigating third-party risk for B2B buyers and suppliers, Utah-based Whistic recently announced a $12 million Series A investment round, FinNSMEs reported. The company offers businesses a platform to manage their third-party partners, connecting users to its Trust Catalog of corporate profiles. Investors at Emergence led the funding, while Album VC and existing backers also participated. Whistic said it would use the investment to grow its staff and scale operations.

CANDIS

Germany’s CANDIS, a small- to medium-sized business (SMB) accounting automation platform, recently announced via press release a $14.2 million

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Turn Data Into Opportunity With These 9 Business Intelligence Tools

Businesses and enterprises have a lot of data to contend with. From acquisition and retention metrics to prospective customers, internal business processes, partners, affiliates, and competitor data, knowing what data matters most to your business can be difficult.

Often, businesses can’t -or simply neglect to -leverage their data effectively into actionable wins that can grow revenue and help them operate more efficiently.

That’s where business intelligence (BI) tools can really help. They pull your data from dozens of sources, clean it up, transform it, and display it visually via dashboards and reports, which are far easier to interpret than raw numbers and fields. BI also makes it easier to track the ins and outs of what’s actually happening in your company.

While BI tools have been around for decades, there’s been an explosion of excellent online tools entering the market in recent years. These tools are constantly evolving to meet

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Data warehouse: a foundation for business intelligence

Businesses are making data analytics a priority like never before — so much so that, according to a recent TDWI study, 82% of businesses are prioritizing their budgets around new technologies and services for analytics and business intelligence.

To derive value from their data, however, companies must efficiently sort through it. A data warehouse can store and organize historical, operational, and transactional data for analytical use, improving data accessibility and enhancing a business’s ability to make bottom-line decisions.

Data warehouse characteristics

A data warehouse is a repository that stores current and historical data from disparate sources. It’s a key component of a data analytics architecture that creates an environment for decision support, analytics, business intelligence, and data mining.

A data warehouse holds data from multiple sources, including internal databases and SaaS platforms. After the data has been loaded, it can be cleansed, transformed, catalogued, and checked for quality before it’s

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Leading the Way in Data Analysis for Business Intelligence

Click to learn more about author Samuel Bocetta.

Companies are implementing business strategies
with some key objectives in mind: cost reduction, improvements in efficiency,
and enhanced profitability.

Business intelligence can add huge value in these areas, which is why professionals in business intelligence and data analysis are in great demand. In a 2017 IBM report, the demand for data scientists in the United States was expected to increase to 28 percent by 2020. Now here we are.

Business intelligence involves the analysis of past and current data in order to provide practical insights for informed decision-making. The data can be diverse depending on needs. For example, it can include sales that result over a specific length of time, client behavior, or operating costs. Data analytics also often involve prescriptive analysis and predictive modeling.

These and other methods are merged by
experienced professionals with artificial intelligence (AI) and machine
learning (ML)

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4 data wrangling tasks in R for advanced beginners

With great power comes not only great responsibility, but often great complexity — and that sure can be the case with R. The open-source R Project for Statistical Computing, a programming language and environment, offers immense capabilities to investigate, manipulate and analyze data. But because of its sometimes complicated syntax, beginners may find it challenging to improve their skills after learning some basics.

If you’re not even at the stage where you feel comfortable doing rudimentary tasks in R, we recommend you head right over to Computerworld’s Beginner’s Guide to R. But if you’ve got some basics down and want to take another step in your R skills development — or just want to see how to do one of these four tasks in R — please read on.

I’ve created a sample data set with three years of revenue and profit data from Apple, Google and Microsoft, looking

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Integrate machine learning and big data into real-time business intelligence with Snowflake and Plotly’s Dash

[This article was first published on R – Modern Data, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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Business intelligence (BI) is an indispensable tool for many, if not most, modern organizations. BI covers an entire gamut of end-to-end activities from data mining to reporting, all carried out with a core goal assisting critical business decision making.

How significant has BI become? One indication of its popularity can be gleaned from this Google Trends chart showing its search popularity over the last five years.

Google Trends Data — BI vs Machine Learning

This chart shows a steady and sizable increase in search volume for BI throughout the last five years. In fact, it has consistently remained above even the volume for

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Data Visualization vs Business Intelligence

Data Visualization vs Business Intelligence

Difference between Data Visualization and Business Intelligence

Data visualization is the graphical representation of the data and information, extracted from data mining using the visual elements like graph, chart, and maps, data visualization tool, and techniques helps in analyzing massive amount of information and make decision on top of it whereas business intelligence uses the data from the business operations and transform the raw data into the meaningful information, it is used for data analytics, data mining and big data to operate the business.

Data Visualization

I would like to define Data visualization as It is the process of interacting with clients to understand patterns, trends, and insights by transforming data into a visual context.  Data visualization is to generate visuals from the data. It can be in any form like tables, graphs, charts, images, patterns, movies, etc.

  • Data visualization represents information so that it can be seen, in
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On-Premise Reporting, KPIs & Dashboard | Data Analytics | Business Intelligence


IntelliFront BI™ is a browser-based Data Analytics & Business Intelligence solution that saves you time and money by creating & sharing your Reports, KPIs & Dashboards in a single easy-to-use portal. Quickly create static & real-time reports in the browser-based admin module and easily share them with management & stakeholders in their secure user portal. 

Designed with on-premise implementation in mind, it comes with Active Directory Integration, Single Sign On & 2-Factor Authentication as standard. Coupled with its built-in Application Security, IntelliFront BI allows you to collaborate & share reports with external users without compromising your security policies. 

Integration with ChristianSteven’s scheduling suite allows you to automate the export and delivery of reports in standard formats like PDF, CSV & XML to a variety of destinations like Email, Printer, FAX, Folder, Google Sheets, Google Drive, Sharepoint Dropbox, Slack & more.

Easy To Use

Beautiful Dashboards with IntelliFront BI

Video: See how this dashboard was created

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