Guide Might Be Bi Part One

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Because of biphobia and bi erasure, bisexual people suffer significantly higher rates of depression and anxiety, domestic violence, sexual assault, and poverty than lesbians, gay men, or straight cisgender non-transgender people.

Connecting to Data in Power BI Desktop

Bisexuals also face major health disparities and poor healthcare outcomes from a lack of adequate preventative care. There are also several national organizations that advocate specifically for bisexual people. Bisexual FAQ Share this. Filed under: Bisexual , Coming Out. What does bisexual mean? How many people are bisexual? Analysts should be freed up to do the higher value tasks — actual analysis — and automation can help by doing the heavy lifting.

Analysts generally approach data discovery with a question and end goal in mind, so the tool they use should provide them with the ability to apply a targeted and even complex query to the data and be served up the relevant insights they were looking for. With the machine sifting through millions of data points at incredible speeds, the analyst is released from the painfully slow hunting to do the valuable delivery and interpretation of the data.

Business users often need data insights almost instantly and they should be complete with explanations that help the user to interpret what the action point should be as a result.

This is where natural language explanation can assist in the interpretation of that data. It's not just all about the machine when it comes to natural language, the context can often happen outside the data and therefore need to be user-driven. Integrating collaboration capabilities enables users to add their own commentary and further external insights to those that are machine generated.

Even when leveraging the machine, the analysis parameters should be able to be defined by the user. This would help prevent the tool from throwing every related data point at the user with the expectation that they will sift through all of them to find the one thing that is relevant. The tool's inbuilt feedback loop should then help the technology to improve the relevance of the insights to each user.

With the continued advancement of machine learning and AI in the BI space, you should now be looking for proactive, automated insights. With new automated data discovery products like Yellowfin Signals, users no longer need to check unchanging dashboards, but can be instantly alerted changes in their data — trend changes, outliers, step changes etc.

These are automatically generated by the automation technology, based on data changes that fall outside the norms in your historical data. These automated alerts will come with added contextual tools that allow the user to add further context that can be shared among the team and wider enterprise.

In the BI and analytics self-service world of today, a lack of adoption of the BI tools across the enterprise is a stubborn barrier to the growth of businesses. With barely half of those who have access to data actively accessing the data insights, the vast majority of businesses are still operating on a large portion of gut feel.

Over the past decade, adoption has continued to plague the industry despite rapid advances in the speed and sophistication of technologies available. Data is becoming ever more voluminous, is being delivered faster, and comes in staggering variety. All of this increases the complexity of the data and the queries that therefore need to be formed to extract insights.

So, in truth, the advancements in analytics technology have barely kept pace with the growth of the data itself. This means that analytics tools, although more accessible, still require specialist skills to be made truly useful. But we can now begin to see that augmented analysis and automation could be the solution to the adoption issue. When automation is available to everyone in the enterprise and the grunt work of getting insights is lifted, adoption should see an increase as more people benefit from the BI tools and insights without the effort previously required.

Automation will help remove the barriers of difficult interfaces because the insights will be delivered proactively as notifications and with context provided in natural language. With these freedoms, businesses can expect to see a huge increase in the number of employees interacting with data insights that will inform the everyday business decision making.

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With data underpinning the decisions, businesses will see an increase in optimization and therefore be able to compete more effectively. Automation in the BI industry will also dramatically decrease the time to insights as machines can sift through vast volumes of data more accurately and in a fraction of the time that a human can. Data analysts can therefore run more queries and dig deeper into the data answering questions that couldn't be asked before without enormous manpower. And with the integration of data science models directly within the BI platform, businesses will quickly be able to see the value of the predictive data models as they are applied directly to the corporate data.

This technology is about freeing people from the tedious tasks to do the high value work. Automation is making insights accessible and providing a response when a question is raised. Part 1: The state of BI adoption today. Part 2: How we got to the era of augmented analytics. Part 3: The four main blockers to BI adoption.

Discover Yellowfin Signals - automated data discovery designed to get you to insights in an instant. Please complete the form below to request your copy of Yellowfin today. Lucky me? You are commenting using your WordPress. You are commenting using your Google account. You are commenting using your Twitter account. You are commenting using your Facebook account. Notify me of new comments via email. Notify me of new posts via email. This site uses Akismet to reduce spam.

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Might Be Bi Part One : Keith Thomas Walker :

Skip to content. Attraction in the Ace Community Sexual attraction. Share this: Twitter Facebook. Like this: Like Loading About Elizabeth Elizabeth is a something asexual woman who is often mistaken for a lesbian, due to the fact that she is partnered to a lady. She is actually bi but not biromantic and somewhere on the aromantic spectrum. She is formally trained in creative writing with a focus on non-fiction and poetry, and maintains a blog called Prismatic Entanglements, where she mostly writes long-winded personal essays and social criticism.

In her spare time, she enjoys being cat furniture, coming up with new Pokemon strategies and never going to church.


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