"I’ve spent over 6 years building and scaling e-commerce products across EMEA and APAC.
At Jumia, I led product initiatives on the checkout and payments side. For example, I launched gamified promotions on PDP and checkout that improved engagement and delivered a 2.3x uplift in conversion. I also introduced automated installment payments and order cancellation flows, which not only improved user trust but also reduced complaints by 30% and lowered operational costs.
Before that, at Lazada, I work"
Rajeev K. - "I’ve spent over 6 years building and scaling e-commerce products across EMEA and APAC.
At Jumia, I led product initiatives on the checkout and payments side. For example, I launched gamified promotions on PDP and checkout that improved engagement and delivered a 2.3x uplift in conversion. I also introduced automated installment payments and order cancellation flows, which not only improved user trust but also reduced complaints by 30% and lowered operational costs.
Before that, at Lazada, I work"See full answer
"OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) are two types of data processing systems, each designed for specific purposes in the context of database and data warehouse environments.
OLTP (Online Transaction Processing):Purpose: OLTP systems are designed to manage and handle high volumes of transactions, such as inserting, updating, and deleting data. These systems are typically used in day-to-day business operations.
Characteristics: Handles small, si"
Nikunj V. - "OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) are two types of data processing systems, each designed for specific purposes in the context of database and data warehouse environments.
OLTP (Online Transaction Processing):Purpose: OLTP systems are designed to manage and handle high volumes of transactions, such as inserting, updating, and deleting data. These systems are typically used in day-to-day business operations.
Characteristics: Handles small, si"See full answer
"Make current as root.
2 while current is not null,
if p and q are less than current,
go left.
If p and q are greater than current,
go right.
else return current.
return null"
Vaibhav D. - "Make current as root.
2 while current is not null,
if p and q are less than current,
go left.
If p and q are greater than current,
go right.
else return current.
return null"See full answer
"Delta lake is a metadata layer on top of cloud storage which helps giving datalake transactional capabilities. It helps implement upsert/merge as it conforms a schema to the data assets stored in cloud.
It also offers various other capabilities like liquid clustering,time travel, schema evolution,deletes."
Nitish C. - "Delta lake is a metadata layer on top of cloud storage which helps giving datalake transactional capabilities. It helps implement upsert/merge as it conforms a schema to the data assets stored in cloud.
It also offers various other capabilities like liquid clustering,time travel, schema evolution,deletes."See full answer
"function isPalindrome(s, start, end) {
while (s[start] === s[end] && end >= start) {
start++;
end--;
}
return end <= start;
}
function longestPalindromicSubstring(s) {
let longestPalindrome = '';
for (let i=0; i < s.length; i++) {
let j = s.length-1;
while (s[i] !== s[j] && i <= j) {
j--;
}
if (s[i] === s[j]) {
if (isPalindrome(s, i, j)) {
const validPalindrome = s.substring(i, j+1"
Tiago R. - "function isPalindrome(s, start, end) {
while (s[start] === s[end] && end >= start) {
start++;
end--;
}
return end <= start;
}
function longestPalindromicSubstring(s) {
let longestPalindrome = '';
for (let i=0; i < s.length; i++) {
let j = s.length-1;
while (s[i] !== s[j] && i <= j) {
j--;
}
if (s[i] === s[j]) {
if (isPalindrome(s, i, j)) {
const validPalindrome = s.substring(i, j+1"See full answer