diff --git a/docs/strategy-customization.md b/docs/strategy-customization.md
index 221c863ec..260e253c4 100644
--- a/docs/strategy-customization.md
+++ b/docs/strategy-customization.md
@@ -617,9 +617,8 @@ Please always check the mode of operation to select the correct method to get da
 ### *available_pairs*
 
 ``` python
-if self.dp:
-    for pair, timeframe in self.dp.available_pairs:
-        print(f"available {pair}, {timeframe}")
+for pair, timeframe in self.dp.available_pairs:
+    print(f"available {pair}, {timeframe}")
 ```
 
 ### *current_whitelist()*
@@ -653,10 +652,9 @@ This is where calling `self.dp.current_whitelist()` comes in handy.
 
 ``` python
 # fetch live / historical candle (OHLCV) data for the first informative pair
-if self.dp:
-    inf_pair, inf_timeframe = self.informative_pairs()[0]
-    informative = self.dp.get_pair_dataframe(pair=inf_pair,
-                                             timeframe=inf_timeframe)
+inf_pair, inf_timeframe = self.informative_pairs()[0]
+informative = self.dp.get_pair_dataframe(pair=inf_pair,
+                                            timeframe=inf_timeframe)
 ```
 
 !!! Warning "Warning about backtesting"
@@ -671,10 +669,9 @@ It can also be used in specific callbacks to get the signal that caused the acti
 
 ``` python
 # fetch current dataframe
-if self.dp:
-    if self.dp.runmode.value in ('live', 'dry_run'):
-        dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'],
-                                                                 timeframe=self.timeframe)
+if self.dp.runmode.value in ('live', 'dry_run'):
+    dataframe, last_updated = self.dp.get_analyzed_dataframe(pair=metadata['pair'],
+                                                                timeframe=self.timeframe)
 ```
 
 !!! Note "No data available"
@@ -684,11 +681,10 @@ if self.dp:
 ### *orderbook(pair, maximum)*
 
 ``` python
-if self.dp:
-    if self.dp.runmode.value in ('live', 'dry_run'):
-        ob = self.dp.orderbook(metadata['pair'], 1)
-        dataframe['best_bid'] = ob['bids'][0][0]
-        dataframe['best_ask'] = ob['asks'][0][0]
+if self.dp.runmode.value in ('live', 'dry_run'):
+    ob = self.dp.orderbook(metadata['pair'], 1)
+    dataframe['best_bid'] = ob['bids'][0][0]
+    dataframe['best_ask'] = ob['asks'][0][0]
 ```
 
 The orderbook structure is aligned with the order structure from [ccxt](https://github.com/ccxt/ccxt/wiki/Manual#order-book-structure), so the result will look as follows:
@@ -717,12 +713,11 @@ Therefore, using `ob['bids'][0][0]` as demonstrated above will result in using t
 ### *ticker(pair)*
 
 ``` python
-if self.dp:
-    if self.dp.runmode.value in ('live', 'dry_run'):
-        ticker = self.dp.ticker(metadata['pair'])
-        dataframe['last_price'] = ticker['last']
-        dataframe['volume24h'] = ticker['quoteVolume']
-        dataframe['vwap'] = ticker['vwap']
+if self.dp.runmode.value in ('live', 'dry_run'):
+    ticker = self.dp.ticker(metadata['pair'])
+    dataframe['last_price'] = ticker['last']
+    dataframe['volume24h'] = ticker['quoteVolume']
+    dataframe['vwap'] = ticker['vwap']
 ```
 
 !!! Warning
diff --git a/freqtrade/strategy/interface.py b/freqtrade/strategy/interface.py
index f41369189..79dbd4c69 100644
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -617,9 +617,6 @@ class IStrategy(ABC, HyperStrategyMixin):
                 )
                 informative_pairs.append(pair_tf)
             else:
-                if not self.dp:
-                    raise OperationalException('@informative decorator with unspecified asset '
-                                               'requires DataProvider instance.')
                 for pair in self.dp.current_whitelist():
                     informative_pairs.append((pair, inf_data.timeframe, candle_type))
         return list(set(informative_pairs))
@@ -713,10 +710,9 @@ class IStrategy(ABC, HyperStrategyMixin):
             # Defs that only make change on new candle data.
             dataframe = self.analyze_ticker(dataframe, metadata)
             self._last_candle_seen_per_pair[pair] = dataframe.iloc[-1]['date']
-            if self.dp:
-                self.dp._set_cached_df(
-                    pair, self.timeframe, dataframe,
-                    candle_type=self.config.get('candle_type_def', CandleType.SPOT))
+            self.dp._set_cached_df(
+                pair, self.timeframe, dataframe,
+                candle_type=self.config.get('candle_type_def', CandleType.SPOT))
         else:
             logger.debug("Skipping TA Analysis for already analyzed candle")
             dataframe[SignalType.ENTER_LONG.value] = 0
@@ -737,8 +733,6 @@ class IStrategy(ABC, HyperStrategyMixin):
         The analyzed dataframe is then accessible via `dp.get_analyzed_dataframe()`.
         :param pair: Pair to analyze.
         """
-        if not self.dp:
-            raise OperationalException("DataProvider not found.")
         dataframe = self.dp.ohlcv(
             pair, self.timeframe, candle_type=self.config.get('candle_type_def', CandleType.SPOT)
         )