How to Reverse Type 2 Diabetes Naturally? The prevalence of diabetes has hit an all time high, with currently more than 500 million prevalent cases of type 2 diabetes worldwide (1). It was determined in 2015 that diabetes was the seventh leading cause of death in the United States
(2). With statistics like these, it’s no wonder people are researching ways on how to reverse diabetes naturally.When not managed properly, type 2 diabetes can lead to kidney disease, blindness, leg and foot amputations, hearing impairment, skin conditions, nerve damage and even death
(3). But what many do not know, or are not told by their doctors, is that type 2 diabetes is a completely preventable and reversible condition. All it takes is a little diet and lifestyle change.What is Diabetes?Diabetes is a chronic condition in which the body either cannot produce insulin, or it cannot properly use the insulin it produces. Insulin is a hormone released by the pancreas, that controls the amount of glucose (sugar) in the blood
(3).Under normal circumstances, insulin is released by the pancreas to help with the storage of sugar and fats. But when someone has diabetes, insulin doesn’t work as it should, leading to high blood sugar levels and diabetes symptoms.It is important to note that there are major differences between type 1 and type 2 diabetes. Here’s a short explanation of how each type works.Type 1 DiabetesType 1 diabetes, previously known as juvenile diabetes or insulin-dependent diabetes, is an autoimmune disease where the pancreas produces little to no insulin. This happens because the immune system mistakenly destroys the insulin-producing cells in the pancreas (called islets of Langerhans)
(4). Once the pancreatic cells are damaged, insulin can no longer be created (or there is a reduced ability to create insulin).While type 1 diabetes is rarely reversed, blood sugar levels can be improved with the right dietary modifications. As a result, individuals with type 1 diabetes don’t have to depend on their insulin and medications as frequently as they’d have to without changes to their lifestyle.Type 2 DiabetesType 2 diabetes is the most common form of diabetes, mainly because it is caused as a direct result of diet and lifestyle. Type 2 diabetes is caused by insulin resistance, which means that the body doesn’t respond properly when insulin is released
(5). As a result, glucose builds up in the blood, leading to high blood sugar. While the body can keep up for a short period of time by producing more insulin, longer-term, chronic high blood sugar leads to a burn out of insulin receptor sites.According to the National Institute of Diabetes and Digestive and Kidney Diseases, type 2 diabetes usually develops because of the following contributing factors
(6):– Physical inactivity– Poor diet– Being overweight– Having high levels of inflammation in the body– Family history of diabetes– Hormonal problems like Cushing’s syndrome, acromegaly and hyperthyroidism– Exposure to toxins, viruses of harmful chemicals– Taking medications that disrupt insulin productionWhatever the contributing factor, learning how to reverse diabetes naturally will not only help get rid of the symptoms associated with diabetes, but it will also improve other aspects of your health as well.What is Causing
the Diabetes Epidemic?Before we get into how to reverse diabetes naturally, I first want to talk a little bit about what is causing the diabetes epidemic. Let’s start with the most obvious cause – diet.The average American consumes over 156 pounds of added sugar in a year – that’s 17 times more than what we ate 200 years ago. Processed foods, rich in carbohydrates and chemicals add to the refined sugar burden.But it’s not just refined sugar causing the problem – it’s fat, too. Especially the combination of high fat and high sugar foods like cookies, cakes, donuts, pastries, etc.According to Dr. Michael Greger from NutritionFacts.org:“Lower the level of fat in people’s blood and the insulin resistance comes right down. If we clear the fat out of the blood, we also clear the sugar out. That explains the finding that on the high fat, ketogenic diet, insulin doesn’t work very well. Our bodies become insulin resistant. But as the amount of fat in our diet test lower and lower, insulin works better and better — a clear demonstration that the sugar tolerance of even healthy individuals can be impaired by administering a low-carb, high-fat diet. We can decrease insulin resistance, however, by decreasing fat intake.”
We’ll touch more on diet in the 10 steps I’ve outlined below.10 Steps on How to Reverse Diabetes NaturallyKnowing that type 2 diabetes is an acquired condition, makes treating, preventing, and curing it, that much easier. Here are
10 steps on how to reverse diabetes naturally.
1. Remove Refined Sugar from Your DietWhile the opinion that sugar does not cause type 2 diabetes, that doesn’t mean you should start drinking all the soda’s and candy bars you can imagine. Most of the processed foods out there (whether that be donuts, candy bars, etc.) contain plenty of refined sugar, refined grains, as well as fats from oils or lard. Consuming such foods will raise the risk of obesity and type 2 diabetes.According to a review in the Journal of Endocrinology, when we eat too much glucose-containing sugar, the excess glucose our body can’t process quickly enough can increase the levels of pro-inflammatory messengers called cytokines
(7). Chronic inflammation is not only a trigger for the development of insulin resistance (the main cause of type 2 diabetes), but it also leads to illnesses like hypertension, depression, and neurodegenerative disease.Most type 2 diabetics are also instructed to avoid the healthy sugars found in fresh fruit. This is terrible advice, given fruit intake is more protective than anything. In a recent and massive study of over 500,000 subjects followed over 7 years, researchers found that the more frequently subjects ate fruit, the lower was their risk of developing type 2 diabetes
(8). The lead researcher stated that “the sugar in fruit is not the same as the sugar in manufactured foods.”2. Lower the Amount and Type of Fat You EatWhat many diabetics aren’t aware of, is that it is the fat that is the problem when it comes to type 2 diabetes. Nearly 100 years ago, healthy volunteers were split into two groups – half were fed a fat-rich diet, and the other half on a carb-rich diet. Within just two days, the fatty diet groups’ glucose intolerance skyrocketed to amounts twice as high as those fed a carbohydrate-rich diet
(9).Insulin allows sugar in our blood to enter our cells. When insulin attaches to the insulin receptor, it activates a series of enzymatic reactions, which ends with active glucose transport (a gateway for glucose to enter the cell). If our insulin receptors are covered in fat, we end up with high blood sugar, because insulin can’t enter our cells. This is called insulin resistance. This fat is called intramyocellular lipid, or fat inside our muscle cells
(10).The mechanism by which fat (specifically saturated fat) induces insulin resistance wasn’t discovered until MRI techniques were developed to see what was actually happening inside the muscle cells as fat is infused into the blood stream.Studies since shown that the accumulation of fat droplets, and not carbohydrate stores in the liver and muscle cells, contributes to insulin resistance and type 2 diabetes. These droplets result from raising levels of saturated animal fats in the blood, like those found in chicken, beef, cheese, dairy and fish. One hit of saturated animal fat can start causing insulin resistance, inhibiting glucose uptake after just 160 minutes
(11).Even plant-based fats in excess can have the same effect, but the amount of plant-based fats consumed generally isn’t as high as what we see with individuals consuming saturated animal fat.Choose your fat from a clean, plant-based source like avocado, chia seeds, flax seeds, sunflower and pumpkin seeds, as well as nuts. Remember, everything in
moderation.3. Get the Right NutrientsEating real, whole food, is a great place to start when trying to reverse diabetes naturally. Eating a variety of vegetables and fruit of different colors helps reduce inflammation, and increases the amount of fiber you’re getting, which also helps regulate blood sugar (aim for about 30-40 grams of fiber daily).MagnesiumEating magnesium-rich foods like cacao, hemp seeds, pumpkin seeds, spinach, and swiss chard can also help your body metabolize glucose properly
(12). Unfortunately, a lot of the foods we eat are low in magnesium, thanks to poor farming practices and stripping the soil of minerals over the years, so taking a magnesium supplement never hurts! I recommend a magnesium glycinate supplement to ensure it absorbs properly.ChromiumAnother essential nutrient that is involved in normal carbohydrate and lipid metabolism is chromium. It plays an important role in insulin pathways, and helps bring glucose into our cells so that it can be used for energy. It also helps balance out blood glucose levels by improving the glucose tolerance factor in your body
(13). Broccoli contains very high levels of chromium, and is one of the best sources, but foods like green beans, potatoes, tomatoes and oats also contain decent amounts.Alpha Lipoic AcidAlpha lipoic acid (ALA) is an omega-3 fatty acid and antioxidant that helps turn glucose into fuel for the body. It improves insulin sensitivity and also reduces symptoms of diabetic neuropathy.While ALA is found naturally in some food sources like walnuts, flaxseeds, spinach, broccoli and potatoes, it doesn’t produce a noticeable increase in the levels of free ALA in the body.Taking an ALA supplement will increase the amount that circulates in your body, which can be beneficial when trying to naturally reverse diabetes (14).Vitamin
D3Vitamin D deficiency has been linked with a range of serious disease like cancer and type 2 diabetes
(15). Studies have also suggested that low vitamin D also contributes to insulin resistance
(16). While I always recommend getting your vitamin D from the sun, if you live in more Northern climates, you’ll need to supplement with vitamin D3 during the winter months to keep your levels
up!4. Avoid Gluten and DairyGluten-containing grains like wheat can cause high levels of inflammation in the body, particularly the intestinal tract. When the gastrointestinal tract is inflamed, cortisol and leptin are interfered with, which can lead to spikes in blood sugar. Instead, opt for organic versions of pseudo-grains like buckwheat, sorghum, teff, quinoa, and wild rice. If you must eat wheat or other gluten-containing grains, please make sure they are organic and sprouted to avoid glyphosate contamination and improve digestibility.Dairy is another food you want to be weary of. Aside from being high in saturated fat (which can spike blood sugar levels – see point number two above), the protein in dairy (casein) harms the body, and triggers a similar inflammatory immune response as gluten. Thankfully, there are plenty of dairy alternatives out there, like plant-based milks, yogurts and cheeses.
5. Stop Drinking AlcoholAlcohol is another big no-no for diabetics. Alcohol raises blood sugar to dangerously high levels, especially in the case of beer, coolers, liqueurs, and mixes that contain soda. One study found a 43% increased incidence of diabetes associated with “heavy alcohol consumption,” which they defined as three or more drinks a day
(17).6. Herbal and Dietary SupplementsEating foods that help manage blood glucose levels can also help those with type 2 diabetes.Cinnamon is particularly great for reducing fasting glucose levels, as well as reducing bad (LDL) cholesterol
(18). This makes it an ideal food to prevent blood sugar spikes.Bitter Melon, or bitter gourd, is widely recognized for its medicinal properties regarding blood sugar management for diabetics. It helps stimulate the pancreas to produce insulin, and regulates the body’s use of it. Studies have shown that bitter melon extract can reduce and mange symptoms of diabetes, including insulin resistance, kidney damage, blood vessel damage and hormone irregularities
(19).Turmeric is another great herb to supplement with, whether that is in capsule, tincture, or powdered form. Turmeric helps lower levels of inflammation in the body, which, when not controlled, can trigger insulin
resistance.7. Exercise RegularlyGetting enough regular exercise can improve your health and regulate blood sugar levels. You don’t need to go to the gym for hours on end – even 30 minutes a day of walking is enough to help manage symptoms of diabetes. Stretching or doing yoga is also a great way to move the body. If you’re able, you can do high intensity interval training (HIIT) or weight training a couple days a week to help your body burn more fat and naturally increase insulin
sensitivity.8. Get Enough SleepNot getting enough sleep can wreak havoc on all systems in the body. According to Mark Mahowald, MD, “there is some evidence that sleep deprivation could lead to a pre-diabetic state.” Sleep loss disrupts glucose metabolism, leading to reduced insulin sensitivity and glucose intolerance. This can eventually lead to diabetes, if consistently elevated.If you’re having troubles sleeping, try winding down before bed by putting down all electronics at least 1-2 hours before sleep. Blue light can mess with melatonin production (the chemical that helps us sleep), making us a little more restless at night. Herbal teas, essential oils, warm baths, and a little bit of nutmeg can also help you get more shut-eye.9. Control Your StressChronic stress does a number to our hormones, including insulin. Stress hormones increase the production of inflammatory cytokines in the body (20), which is a major contributing factor to diabetes (as well as a host of other diseases). Stress can sometimes lead individuals to over-eat, too, which can exacerbate the problem.Try to control your stress through meditation, yoga, social interaction, making art, listening to music, or simply going for a walk in nature. Essential oils like lavender are also useful in
reducing stress levels.10. Lower Chemical ExposureOther culprits thought to be a major contribution to diabetes are chemicals found in the environment, as well as in products we use daily. Certain chemicals increase the risk of type 2 diabetes, while others contribute to obesity and weight gain. Obesity and weight gain, as you might now know, are serious risk factors in the development of type 2 diabetes.Studies have found links between certain chemicals like phthalates and BPA, as well as PCBs, dioxins and their relationship to diabetes. A study published in the journal Environmental Health Perspectives, found that women with the highest levels of phthalates in their urine had a 70 percent higher risk of diabetes than women with the lowest levels of phthalates circulating in their bodies
(21).Detoxing your home of chemicals is a great way to help reverse or reduce your risk of type 2 diabetes. It will also reduce your risk of developing life-threatening diseases like cancer.Here are some products you should re-consider making or purchasing out of natural products, or ditching altogether:– Pesticides and herbicides (those used on food, and those used for lawn care)– Laundry detergent– Dryer sheets– Fabric softeners– Dish soap– Toothpaste– Paint (used on your walls, or for arts & crafts)– Plastics– Tap water– Air fresheners– Cigarette smoke (first, second and third-hand)– Shampoo/conditioner– Scented candles– Lotions and serums– Household cleaners– Cosmetics– Deodorants– Soap and other toiletries– Sunscreen– Perfumes, colognes and body sprays– Processed foods– Mercury from fish– Gasoline vapors (exposed to more in the city)– Hair and nail salons– Bug sprays– Plastic storage containers– Mattresses made with toxic materials like PBDE– Plastic drink bottles– Non-stick cookware– Dry-cleaned clothes -How to Reverse Type 2 Diabetes Naturally?
How to Reverse Type 2 Diabetes Naturally?
Summary:
When not managed properly, type 2 diabetes can lead to kidney disease, blindness, leg and foot amputations, hearing impairment, skin conditions, nerve damage and even death (3). Chronic inflammation is not only a trigger for the development of insulin resistance (the main cause of type 2 diabetes), but it also leads to illnesses like hypertension, depression, and neurodegenerative disease. Aside from being high in saturated fat (which can spike blood sugar levels – see point number two above), the protein in dairy (casein) harms the body, and triggers a similar inflammatory immune response as gluten...
https://searchbusinessanalytics.techtarget.com/definition/business-intelligence-BI
business intelligence (BI)
Posted by: Margaret Rouse
WhatIs.com
Contributor(s): Craig Stedman and Ed Burns
Business intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions. As part of the BI process, organizations collect data from internal IT systems and external sources, prepare it for analysis, run queries against the data and create data visualizations, BI dashboards and reports to make the analytics results available to business users for operational decision-making and strategic planning.
The ultimate goal of BI initiatives is to drive better business decisions that enable organizations to increase revenue, improve operational efficiency and gain competitive advantages over business rivals. To achieve that goal, BI incorporates a combination of analytics, data management and reporting tools, plus various methodologies for managing and analyzing data.
How the business intelligence process works
A business intelligence architecture includes more than just BI software. Business intelligence data is typically stored in a data warehouse built for an entire organization or in smaller data marts that hold subsets of business information for individual departments and business units, often with ties to an enterprise data warehouse. In addition, data lakes based on Hadoop clusters or other big data systems are increasingly used as repositories or landing pads for BI and analytics data, especially for log files, sensor data, text and other types of unstructured or semistructured data.
BI data can include historical information and real-time data gathered from source systems as it's generated, enabling BI tools to support both strategic and tactical decision-making processes. Before it's used in BI applications, raw data from different source systems generally must be integrated, consolidated and cleansed using data integration and data quality management tools to ensure that BI teams and business users are analyzing accurate and consistent information.
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Ultimate guide to business intelligence in the enterprise
From there, the steps in the BI process include the following:
data preparation, in which data sets are organized and modeled for analysis;
analytical querying of the prepared data;
distribution of key performance indicators (KPIs) and other findings to business users; and
use of the information to help influence and drive business decisions.
Initially, BI tools were primarily used by BI and IT professionals who ran queries and produced dashboards and reports for business users. Increasingly, however, business analysts, executives and workers are using business intelligence platforms themselves, thanks to the development of self-service BI and data discovery tools. Self-service business intelligence environments enable business users to query BI data, create data visualizations and design dashboards on their own.
BI programs often incorporate forms of advanced analytics, such as data mining, predictive analytics, text mining, statistical analysis and big data analytics. A common example is predictive modeling that enables what-if analysis of different business scenarios. In most cases, though, advanced analytics projects are conducted by separate teams of data scientists, statisticians, predictive modelers and other skilled analytics professionals, while BI teams oversee more straightforward querying and analysis of business data.
These five steps are the key parts of the BI process.
Why business intelligence is important
Overall, the role of business intelligence is to improve an organization's business operations through the use of relevant data. Companies that effectively employ BI tools and techniques can translate their collected data into valuable insights about their business processes and strategies. Such insights can then be used to make better business decisions that increase productivity and revenue, leading to accelerated business growth and higher profits.
Without BI, organizations can't readily take advantage of data-driven decision-making. Instead, executives and workers are primarily left to base important business decisions on other factors, such as accumulated knowledge, previous experiences, intuition and gut feelings. While those methods can result in good decisions, they're also fraught with the potential for errors and missteps because of the lack of data underpinning them.
Benefits of business intelligence
A successful BI program produces a variety of business benefits in an organization. For example, BI enables C-suite executives and department managers to monitor business performance on an ongoing basis so they can act quickly when issues or opportunities arise. Analyzing customer data helps make marketing, sales and customer service efforts more effective. Supply chain, manufacturing and distribution bottlenecks can be detected before they cause financial harm. HR managers are better able to monitor employee productivity, labor costs and other workforce data.
Overall, the key benefits that businesses can get from BI applications include the ability to:
speed up and improve decision-making;
optimize internal business processes;
increase operational efficiency and productivity;
spot business problems that need to be addressed;
identify emerging business and market trends;
develop stronger business strategies;
drive higher sales and new revenues; and
gain a competitive edge over rival companies.
BI initiatives also provide narrower business benefits -- among them, making it easier for project managers to track the status of business projects and for organizations to gather competitive intelligence on their rivals. In addition, BI, data management and IT teams themselves benefit from business intelligence, using it to analyze various aspects of technology and analytics operations.
Types of business intelligence tools and applications
Business intelligence combines a broad set of data analysis applications designed to meet different information needs. Most are supported by both self-service BI software and traditional BI platforms. The list of BI technologies that are available to organizations includes the following:
Ad hoc analysis. Also known as ad hoc querying, this is one of the foundational elements of modern BI applications and a key feature of self-service BI tools. It's the process of writing and running queries to analyze specific business issues. While ad hoc queries are typically created on the fly, they often end up being run regularly, with the analytics results incorporated into dashboards and reports.
Online analytical processing (OLAP). One of the early BI technologies, OLAP tools enable users to analyze data along multiple dimensions, which is particularly suited to complex queries and calculations. In the past, the data had to be extracted from a data warehouse and stored in multidimensional OLAP cubes, but it's increasingly possible to run OLAP analyses directly against columnar databases.
Mobile BI. Mobile business intelligence makes BI applications and dashboards available on smartphones and tablets. Often used more to view data than to analyze it, mobile BI tools typically are designed with an emphasis on ease of use. For example, mobile dashboards may only display two or three data visualizations and KPIs so they can easily be viewed on a device's screen.
Real-time BI. In real-time BI applications, data is analyzed as it's created, collected and processed to give users an up-to-date view of business operations, customer behavior, financial markets and other areas of interest. The real-time analytics process often involves streaming data and supports decision analytics uses, such as credit scoring, stock trading and targeted promotional offers.
Operational intelligence (OI). Also called operational BI, this is a form of real-time analytics that delivers information to managers and frontline workers in business operations. OI applications are designed to aid in operational decision-making and enable faster action on issues -- for example, helping call center agents to resolve problems for customers and logistics managers to ease distribution bottlenecks.
Software-as-a-service BI. SaaS BI tools use cloud computing systems hosted by vendors to deliver data analysis capabilities to users in the form of a service that's typically priced on a subscription basis. Also known as cloud BI, the SaaS option increasingly offers multi-cloud support, which enables organizations to deploy BI applications on different cloud platforms to meet user needs and avoid vendor lock-in.
Open source BI (OSBI). Business intelligence software that is open source typically includes two versions: a community edition that can be used free of charge and a subscription-based commercial release with technical support by the vendor. BI teams can also access the source code for development uses. In addition, some vendors of proprietary BI tools offer free editions, primarily for individual users.
Embedded BI. Embedded business intelligence tools put BI and data visualization functionality directly into business applications. That enables business users to analyze data within the applications they use to do their job. Embedded analytics features are most commonly incorporated by application software vendors, but corporate software developers can also include them in homegrown applications.
Collaborative BI. This is more of a process than a specific technology. It involves the combination of BI applications and collaboration tools to enable different users to work together on data analysis and share information with one another. For example, users can annotate BI data and analytics results with comments, questions and highlighting via the use of online chat and discussion tools.
Location intelligence (LI). This is a specialized form of BI that enables users to analyze location and geospatial data, with map-based data visualization functionality incorporated. Location intelligence offers insights on geographic elements in business data and operations. Potential uses include site selection for retail stores and corporate facilities, location-based marketing and logistics management.
Business intelligence vendors and market
Self-service BI and data visualization tools have become the standard for modern BI software. Tableau, Qlik and Spotfire, which is now part of Tibco Software, took the lead in developing self-service technology early and became prominent competitors in the BI market by 2010. Most vendors of traditional BI query and reporting tools have followed in their path since then. Now, virtually every major BI tool incorporates self-service features, such as visual data discovery and ad hoc querying.
In addition, modern BI platforms typically include:
data visualization software for designing charts and other infographics to show data in an easy-to-grasp way;
tools for building BI dashboards, reports and performance scorecards that display visualized data on KPIs and other business metrics;
data storytelling features for combining visualizations and text in presentations for business users; and
usage monitoring, performance optimization, security controls and other functions for managing BI deployments.
BI tools are available from dozens of vendors overall. Major IT vendors that offer BI software include IBM, Microsoft, Oracle, SAP, SAS and Salesforce, which bought Tableau in 2019 and also sells its own tools developed before the acquisition. Google is also in the BI market through its Looker unit, acquired in 2020. Other notable BI vendors include Alteryx, Domo, GoodData, Infor Birst, Information Builders, Logi Analytics, MicroStrategy, Pyramid Analytics, Sisense, ThoughtSpot and Yellowfin.
While full-featured BI platforms are the most widely used business intelligence technology, the BI market also includes other product categories. Some vendors offer tools specifically for embedded BI uses; examples include GoodData and Logi Analytics. Companies like Looker, Sisense and ThoughtSpot target complex and curated data analysis applications. Various dashboard and data visualization specialists focus on those parts of the BI process; other vendors specialize in data storytelling tools.
Examples of business intelligence use cases
In general terms, enterprise BI use cases include:
monitoring business performance or other types of metrics;
supporting decision-making and strategic planning;
evaluating and improving business processes;
giving operational workers useful information about customers, equipment, supply chains and other elements of business operations; and
detecting trends, patterns and relationships in data.
Specific use cases and BI applications vary from industry to industry. For example, financial services firms and insurers use BI for risk analysis during the loan and policy approval processes and to identify additional products to offer to existing customers based on their current portfolios. BI helps retailers with marketing campaign management, promotional planning and inventory management, while manufacturers rely on BI for both historical and real-time analysis of plant operations and to help them manage production planning, procurement and distribution.
Airlines and hotel chains are big users of BI for things such as tracking flight capacity and room occupancy rates, setting and adjusting prices, and scheduling workers. In healthcare organizations, BI and analytics aid in the diagnosis of diseases and other medical conditions and in efforts to improve patient care and outcomes. Universities and school systems tap BI to monitor overall student performance metrics and identify individuals who might need assistance, among other applications.
Business intelligence for big data
BI platforms are increasingly being used as front-end interfaces for big data systems that contain a combination of structured, unstructured and semistructured data. Modern BI software typically offers flexible connectivity options, enabling it to connect to a range of data sources. This, along with the relatively simple user interface (UI) in most BI tools, makes it a good fit for big data architectures.
Users of BI tools can access Hadoop and Spark systems, NoSQL databases and other big data platforms, in addition to conventional data warehouses, and get a unified view of the diverse data stored in them. That enables a broad number of potential users to get involved in analyzing sets of big data, instead of highly skilled data scientists being the only ones with visibility into the data.
Alternatively, big data systems serve as staging areas for raw data that later is filtered and refined and then loaded into a data warehouse for analysis by BI users.
Business intelligence trends
In addition to BI managers, business intelligence teams generally include a mix of BI architects, BI developers, BI analysts and BI specialists who work closely with data architects, data engineers and other data management professionals. Business analysts and other end users are also often included in the BI development process to represent the business side and make sure its needs are met.
To help with that, a growing number of organizations are replacing traditional waterfall development with Agile BI and data warehousing approaches that use Agile software development techniques to break up BI projects into small chunks and deliver new functionality on an incremental and iterative basis. Doing so enables companies to put BI features into use more quickly and to refine or modify development plans as business needs change or new requirements emerge.
Other notable trends in the BI market include the following:
The proliferation of augmented analytics technologies. BI tools increasingly offer natural language querying capabilities as an alternative to writing queries in SQL or another programming language, plus AI and machine learning algorithms that help users find, understand and prepare data and create charts and other infographics.
Low-code and no-code development. Many BI vendors are also adding graphical tools that enable BI applications to be developed with little or no coding.
Increased use of the cloud. BI systems initially were slow to move to the cloud, partly because data warehouses were primarily deployed in on-premises data centers. But cloud deployments of both data warehouses and BI tools are growing; in early 2020, consulting firm Gartner said most new BI spending is now for cloud-based projects.
Efforts to improve data literacy. With self-service BI broadening the use of business intelligence tools in organizations, it's critical to ensure that new users can understand and work with data. That's prompting BI teams to include data literacy skills in user training programs. BI vendors have also launched initiatives, such as the Qlik-led Data Literacy Project.
A timeline of notable BI developments
Business intelligence vs. data analytics and business analytics
Sporadic use of the term business intelligence dates back to at least the 1860s, but consultant Howard Dresner is credited with first proposing it in 1989 as an umbrella phrase for applying data analysis techniques to support business decision-making processes. What came to be known as BI tools evolved from earlier, often mainframe-based analytics technologies, such as decision support systems and executive information systems that were primarily used by business executives.
Business intelligence is sometimes used interchangeably with business analytics. In other cases, business analytics is used either more narrowly to refer to advanced analytics or more broadly to include both that and BI. Meanwhile, data analytics is primarily an umbrella term that encompasses all forms of BI and analytics applications. That includes the main types of data analysis: descriptive analytics, which is typically what BI provides; predictive analytics, which models future behavior and outcomes; and prescriptive analytics, which recommends business actions.
Comparison of BI and advanced analytics
This was last updated in September 2020
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