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10 top data and analytics tech trends for 2019<\/h2>
Augmented analytics, continuous intelligence, data fabric and persistent memory servers are among the emerging trends that will drive the advancement of analytics over the next few years, says Gartner.<\/p>

About these technology trends<\/h2>
In their presentation at the Gartner Data & Analytics Summit in Sydney, Australia, this week, Gartner analysts Donald Feinberg and Rita Sallam released their list of the "Top Technology Trends in Data and Analytics That Will Change Your Business."<\/p>

1. Augmented analytics<\/h2>
By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence as well as data science and machine learning platforms, and of embedded analytics.<\/p>

2. Augmented data management<\/h2>
By 2020, 50 percent of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.<\/p>

3. Continuous intelligence<\/h2>
By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.<\/p>

4. Explainable AI<\/h2>
By 2022, 75 percent of new end user solutions leveraging artificial intelligence and machine learning techniques will be built with commercial instead of open-source platforms.<\/p>

5. Graph analytics<\/h2>
By 2023, over 75 percent of large organizations will hire artificial intelligence behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.<\/p>

6. Data fabric<\/h2>
The application of graph processing and graph databases will grow at 100 percent annually through 2022 to continuously accelerate data preparation, and enable more complex and adaptive data science.<\/p>

7. Natural language processing (NLP)\/conversational analytics<\/h2>
Through 2022, data management manual tasks will be reduced by 45 percent through the addition of machine learning and automated service level management.<\/p>

8. Commercial AI and machine learning<\/h2>
Through 2022, custom-made data fabric designs will be deployed as static infrastructure, forcing a new wave of cost to completely redesign for more dynamic approaches.<\/p>

9. Blockchain<\/h2>
By 2021, most permissioned blockchain uses will be replaced by ledger DBMS products.<\/p>

10. Persistent memory servers<\/h2>
By 2021, persistent memory will represent more than 10 percent of in-memory computing memory GB consumption.<\/p>

","saveContent":"

10 top data and analytics tech trends for 2019<\/h2>
Augmented analytics, continuous intelligence, data fabric and persistent memory servers are among the emerging trends that will drive the advancement of analytics over the next few years, says Gartner.<\/p>

About these technology trends<\/h2>
In their presentation at the Gartner Data & Analytics Summit in Sydney, Australia, this week, Gartner analysts Donald Feinberg and Rita Sallam released their list of the "Top Technology Trends in Data and Analytics That Will Change Your Business."<\/p>

1. Augmented analytics<\/h2>
By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence as well as data science and machine learning platforms, and of embedded analytics.<\/p>

2. Augmented data management<\/h2>
By 2020, 50 percent of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.<\/p>

3. Continuous intelligence<\/h2>
By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.<\/p>

4. Explainable AI<\/h2>
By 2022, 75 percent of new end user solutions leveraging artificial intelligence and machine learning techniques will be built with commercial instead of open-source platforms.<\/p>

5. Graph analytics<\/h2>
By 2023, over 75 percent of large organizations will hire artificial intelligence behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.<\/p>

6. Data fabric<\/h2>
The application of graph processing and graph databases will grow at 100 percent annually through 2022 to continuously accelerate data preparation, and enable more complex and adaptive data science.<\/p>

7. Natural language processing (NLP)\/conversational analytics<\/h2>
Through 2022, data management manual tasks will be reduced by 45 percent through the addition of machine learning and automated service level management.<\/p>

8. Commercial AI and machine learning<\/h2>
Through 2022, custom-made data fabric designs will be deployed as static infrastructure, forcing a new wave of cost to completely redesign for more dynamic approaches.<\/p>

9. Blockchain<\/h2>
By 2021, most permissioned blockchain uses will be replaced by ledger DBMS products.<\/p>

10. Persistent memory servers<\/h2>
By 2021, persistent memory will represent more than 10 percent of in-memory computing memory GB consumption.<\/p>

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10 top data and analytics tech trends for 2019<\/h2>Augmented analytics, continuous intelligence, data fabric and persistent memory servers are among the emerging trends that will drive the advancement of analytics over the next few years, says Gartner.<\/p>

About these technology trends<\/h2>In their presentation at the Gartner Data & Analytics Summit in Sydney, Australia, this week, Gartner analysts Donald Feinberg and Rita Sallam released their list of the "Top Technology Trends in Data and Analytics That Will Change Your Business."<\/p>

1. Augmented analytics<\/h2>By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence as well as data science and machine learning platforms, and of embedded analytics.<\/p>

2. Augmented data management<\/h2>By 2020, 50 percent of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.<\/p>

3. Continuous intelligence<\/h2>By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.<\/p>

4. Explainable AI<\/h2>By 2022, 75 percent of new end user solutions leveraging artificial intelligence and machine learning techniques will be built with commercial instead of open-source platforms.<\/p>

5. Graph analytics<\/h2>By 2023, over 75 percent of large organizations will hire artificial intelligence behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.<\/p>

6. Data fabric<\/h2>The application of graph processing and graph databases will grow at 100 percent annually through 2022 to continuously accelerate data preparation, and enable more complex and adaptive data science.<\/p>

7. Natural language processing (NLP)\/conversational analytics<\/h2>Through 2022, data management manual tasks will be reduced by 45 percent through the addition of machine learning and automated service level management.<\/p>

8. Commercial AI and machine learning<\/h2>Through 2022, custom-made data fabric designs will be deployed as static infrastructure, forcing a new wave of cost to completely redesign for more dynamic approaches.<\/p>

9. Blockchain<\/h2>By 2021, most permissioned blockchain uses will be replaced by ledger DBMS products.<\/p>

10. Persistent memory servers<\/h2>By 2021, persistent memory will represent more than 10 percent of in-memory computing memory GB consumption.<\/p>","saveContent":"

10 top data and analytics tech trends for 2019<\/h2>Augmented analytics, continuous intelligence, data fabric and persistent memory servers are among the emerging trends that will drive the advancement of analytics over the next few years, says Gartner.<\/p>

About these technology trends<\/h2>In their presentation at the Gartner Data & Analytics Summit in Sydney, Australia, this week, Gartner analysts Donald Feinberg and Rita Sallam released their list of the "Top Technology Trends in Data and Analytics That Will Change Your Business."<\/p>

1. Augmented analytics<\/h2>By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence as well as data science and machine learning platforms, and of embedded analytics.<\/p>

2. Augmented data management<\/h2>By 2020, 50 percent of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.<\/p>

3. Continuous intelligence<\/h2>By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.<\/p>

4. Explainable AI<\/h2>By 2022, 75 percent of new end user solutions leveraging artificial intelligence and machine learning techniques will be built with commercial instead of open-source platforms.<\/p>

5. Graph analytics<\/h2>By 2023, over 75 percent of large organizations will hire artificial intelligence behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.<\/p>

6. Data fabric<\/h2>The application of graph processing and graph databases will grow at 100 percent annually through 2022 to continuously accelerate data preparation, and enable more complex and adaptive data science.<\/p>

7. Natural language processing (NLP)\/conversational analytics<\/h2>Through 2022, data management manual tasks will be reduced by 45 percent through the addition of machine learning and automated service level management.<\/p>

8. Commercial AI and machine learning<\/h2>Through 2022, custom-made data fabric designs will be deployed as static infrastructure, forcing a new wave of cost to completely redesign for more dynamic approaches.<\/p>

9. Blockchain<\/h2>By 2021, most permissioned blockchain uses will be replaced by ledger DBMS products.<\/p>

10 top data and analytics tech trends for 2019<\/h2>
Augmented analytics, continuous intelligence, data fabric and persistent memory servers are among the emerging trends that will drive the advancement of analytics over the next few years, says Gartner.<\/p>

About these technology trends<\/h2>
In their presentation at the Gartner Data & Analytics Summit in Sydney, Australia, this week, Gartner analysts Donald Feinberg and Rita Sallam released their list of the "Top Technology Trends in Data and Analytics That Will Change Your Business."<\/p>

1. Augmented analytics<\/h2>
By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence as well as data science and machine learning platforms, and of embedded analytics.<\/p>

2. Augmented data management<\/h2>
By 2020, 50 percent of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.<\/p>

3. Continuous intelligence<\/h2>
By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.<\/p>

4. Explainable AI<\/h2>
By 2022, 75 percent of new end user solutions leveraging artificial intelligence and machine learning techniques will be built with commercial instead of open-source platforms.<\/p>

5. Graph analytics<\/h2>
By 2023, over 75 percent of large organizations will hire artificial intelligence behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.<\/p>

6. Data fabric<\/h2>
The application of graph processing and graph databases will grow at 100 percent annually through 2022 to continuously accelerate data preparation, and enable more complex and adaptive data science.<\/p>

7. Natural language processing (NLP)\/conversational analytics<\/h2>
Through 2022, data management manual tasks will be reduced by 45 percent through the addition of machine learning and automated service level management.<\/p>

8. Commercial AI and machine learning<\/h2>
Through 2022, custom-made data fabric designs will be deployed as static infrastructure, forcing a new wave of cost to completely redesign for more dynamic approaches.<\/p>

9. Blockchain<\/h2>
By 2021, most permissioned blockchain uses will be replaced by ledger DBMS products.<\/p>

10. Persistent memory servers<\/h2>
By 2021, persistent memory will represent more than 10 percent of in-memory computing memory GB consumption.<\/p>

","saveContent":"

10 top data and analytics tech trends for 2019<\/h2>
Augmented analytics, continuous intelligence, data fabric and persistent memory servers are among the emerging trends that will drive the advancement of analytics over the next few years, says Gartner.<\/p>

About these technology trends<\/h2>
In their presentation at the Gartner Data & Analytics Summit in Sydney, Australia, this week, Gartner analysts Donald Feinberg and Rita Sallam released their list of the "Top Technology Trends in Data and Analytics That Will Change Your Business."<\/p>

1. Augmented analytics<\/h2>
By 2020, augmented analytics will be a dominant driver of new purchases of analytics and business intelligence as well as data science and machine learning platforms, and of embedded analytics.<\/p>

2. Augmented data management<\/h2>
By 2020, 50 percent of analytical queries will be generated via search, natural language processing or voice, or will be automatically generated.<\/p>

3. Continuous intelligence<\/h2>
By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.<\/p>

4. Explainable AI<\/h2>
By 2022, 75 percent of new end user solutions leveraging artificial intelligence and machine learning techniques will be built with commercial instead of open-source platforms.<\/p>

5. Graph analytics<\/h2>
By 2023, over 75 percent of large organizations will hire artificial intelligence behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.<\/p>

6. Data fabric<\/h2>
The application of graph processing and graph databases will grow at 100 percent annually through 2022 to continuously accelerate data preparation, and enable more complex and adaptive data science.<\/p>

7. Natural language processing (NLP)\/conversational analytics<\/h2>
Through 2022, data management manual tasks will be reduced by 45 percent through the addition of machine learning and automated service level management.<\/p>

8. Commercial AI and machine learning<\/h2>
Through 2022, custom-made data fabric designs will be deployed as static infrastructure, forcing a new wave of cost to completely redesign for more dynamic approaches.<\/p>

9. Blockchain<\/h2>
By 2021, most permissioned blockchain uses will be replaced by ledger DBMS products.<\/p>

10 top data and analytics trends for 2019

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